arg_1
stringlengths 4
5.08k
| round_1
float64 2
8
⌀ | ann_1
float64 1
2
⌀ | arg_2
stringlengths 8
2.19k
| round_2
float64 1
7
⌀ | ann_2
float64 1
2
⌀ | annotation_name
stringclasses 131
values | is_attacks
int64 0
1
|
|---|---|---|---|---|---|---|---|
The experimental system was described in more detail, and various modes of discharge ignition were analyzed.
| 2 | 1 |
Please describe better your experimental system, such as ignition energy.
| 1 | 2 |
nano12040652_perova
| 1 |
In our preliminary studies, as well as in the papers of other authors, it was found that during pulsed discharges of short duration, the electrode material determines the composition of the vapors that evaporate from the electrodes and diffuse into the gap, including due to shock waves and turbulence. Since under these conditions diffuse discharges, at which the voltage across the gap remains high are formed, metal vapors are excited and ionized together with gas molecules in the discharge gap. This leads to the emission of radiation at various spectral transitions of metal atoms. Only a part of these transitions has a high radiation intensity in the region of interest to researchers. Also, to obtain a high intensity of radiation, transitions of atoms in metal vapors can be used, which are populated as a result of the efficient transfer of energy from excited gas molecules and atoms. Metals, the color of the emission of vapors of which, when excited in the plasma of nanosecond discharges, corresponds to the color of high-altitude atmospheric discharges, were chosen as the material of the electrodes.
| 2 | 1 |
The choice of the electrode material should be clearly explained in the present paper.
| 1 | 2 |
nano12040652_perova
| 1 |
The color of the glow of the discharge plasma at electrodes made of various metals is associated with excitation certain energy levels of particles in the vapors of these metals. So, when using electrodes made of aluminum, steel and copper, we observed the glow of red, blue and green colors, respectively. The different colors of the discharge when changing the material of the electrodes are determined not by the spark or arc stages, but by bright spots on the electrodes, which are formed due to the explosive emission of electrons [Mesyats, G.A. Ecton mechanism of the vacuum arc cathode spot. IEEE transactions on plasma science, 1995, 23(6), pp. 879-883. (DOI: 10.1109/27.476469)]. These areas in the photographs have a bright white color (see, for example, the photographs in Figures 3, 6, 7). In spark or arc discharge, as well as in bright spots the electrodes are locally heated to a high temperature, which leads to the evaporation of the electrode material. High-temperature zones on the electrodes also supply micro- and nanoparticles into a discharge gap. However, emission of individual particles is determined by their temperature, it corresponds to the Planck radiation and is broadband. We note once again that in this work, to obtain metal vapors, as well as metal nano- and microparticles, a pulsed nanosecond discharge in a non-uniform electric field was used.
| 2 | 1 |
Please explain the mechanism of different color arcs produced by electrodes of different materials.
| 1 | 2 |
nano12040652_perova
| 1 |
Several references was added.
| 2 | 1 |
most of the results provided consist in photographs of the discharges: while these are clear and descriptive, they provide a qualitative information only. A spectral analysis is given for one discharge only (discharge in air with a copper electrode): more quantitative results, such as a spectral analysis of the other discharges also, would be helpful for the comparison between the discharges produced in the lab and the ones observed in the atmosphere.
| 1 | 2 |
nano12040652_perova
| 1 |
The main experiments were carried out with discharges in air, and the air pressure was chosen close to the pressures of high-altitude discharges. Other gases, such as argon, were chosen to better demonstrate the discoloration of the discharge.
| 2 | 1 |
A point that should be clarified is the choice of the gases used for the discharges. One would expect a comparison between discharges that happen in gas mixtures of similar composition. Is there any relationship between the specific choice of gases made by the authors and the composition of the atmosphere at the altitudes where the atmospheric discharges take place?
| 1 | 2 |
nano12040652_perova
| 1 |
The manuscript has been revised. This judgment was removed from the text of the manuscript.
| 2 | 1 |
A couple of requests of clarification about specific parts of the text are also provided in the following. Page 5, line 168 The authors state: “An increase in the track brightness is apparently determined by an increase in the particle charge and size due to the evaporation of metal from the surface.” The sense of this sentence is not completely clear to me. Where does the evaporation of the metal take place? It it took place on the particle surface, it should produce a reduction of its size, rather than an increase.
| 1 | 2 |
nano12040652_perova
| 1 |
Thanks for the advice. We plan to do this in our next work.
| 2 | 1 |
Page 6, line 218 The authors state: “Particles of metal and its compounds with oxygen and nitrogen with a size of 500 nm and less are nonuniformly distributed on the surface of the slide”. Some data should be provided to show the elemental composition of the particles.
| 1 | 2 |
nano12040652_perova
| 1 |
The second part of this analysis, titled: “Body composition assessment in Mexican children and adolescents. Part 2: Cross-validation of three bio-electrical impedance methods against dual X-ray absorptiometry for whole-body and regional body composition”, has already been accepted by Nutrients #1604578. The two analyses were conducted on the same children’s database and closely complement each other. As the accepted manuscript already includes the phrase ‘Part 2’ we prefer to keep ‘Part 1’ here ABSTRACT 2.
| 2 | 1 |
TITLE The “Part 1” in the title, while perhaps intriguing, calls for some explanation of future directions. This does not seem to be addressed in the article, thus there seems to be no reason to include this phrase in the title.
| 1 | 2 |
nu14051073_makarova
| 1 |
Corrected, we adjusted this paragraph together with the next one to give a clearer explanation of the motivation of this study.
| 2 | 1 |
Also, the difference(s) between FFM and LM definitions are nuanced and complex and should either be defined, or alternate text should be used here. It seems that the authors are simply trying to point out that use of the 4C model is not common and that other methods are normally used. Best to clarify this statement. INTRODUCTION P2 L61: FFM is obtained via the 4C model – it is not a surrogate.
| 1 | 2 |
nu14051073_makarova
| 1 |
We have adjusted accordingly. We hope now we can give a clearer explanation about the motivation of this study.
| 2 | 1 |
P2 L69: The aim stated here does not follow the logic of the preceding statements in the paragraph, i.e., what does comparing BC methods have to do with lack of healthcare or technology? Is the focus then on finding low cost, easy to apply methods? The aim (and intent) of the study seems too simplistic as stated here – merely comparing methods. How would the results be applied to the healthcare situation in Mexico? These topics should be tied together or an alternative motivation needs to be presented.
| 1 | 2 |
nu14051073_makarova
| 1 |
Clarified in lines 164.
| 2 | 1 |
Who was asked to assent? MATERIALS AND METHODS P3 L94: This is awkwardly worded.
| 1 | 2 |
nu14051073_makarova
| 1 |
The data used was total body with head, as recommended for the ISCD when using DXA for body composition instead of for bone densitometry. We clarified and referenced this in the text, lines 204-208.
| 2 | 1 |
P3 L125: DXA: Was the head ROI excluded from the analyses (as per recommendation by the ISCD)? If so, it should be stated. If not, DXA analysis should be redone and all relationships recalculated.
| 1 | 2 |
nu14051073_makarova
| 1 |
This was a typo, we corrected it. Line 260.
| 2 | 1 |
P5 L176: “(n=52?? )” Is there uncertainty of the number of participants or is this merely a typo?
| 1 | 2 |
nu14051073_makarova
| 1 |
We corrected (lines 287-288).
| 2 | 1 |
P5 L207: The means of FM would be compared using t-test, not calculated.
| 1 | 2 |
nu14051073_makarova
| 1 |
Indeed, it was like that. We have changed it to show only the data of the 288 subjects (without the 5 outliers).
| 2 | 1 |
Are the n values incorrect or is the entire cohort presented here? RESULTS Table 1: The n values in the column headers add up to 293 rather than 288.
| 1 | 2 |
nu14051073_makarova
| 1 |
This was because of the inclusion of the 5 outliers in table 1, which has been corrected.
| 2 | 1 |
Table 1; Body Composition Variables: The mean values do not all agree with those in supplementary Table 1.
| 1 | 2 |
nu14051073_makarova
| 1 |
We have
| 2 | 1 |
Table 1; MRI subsample: There is no indication of age, BMI, etc. in this group. That information may be helpful, perhaps also as supplementary data.
| 1 | 2 |
nu14051073_makarova
| 1 |
Added, the analysis was for the total sample and by subgroups by age and sex, line 287 14.
| 2 | 1 |
P7 L226: It would be helpful if it was made clear that this refers to comparisons of means of all subjects (not broken down by age, sex).
| 1 | 2 |
nu14051073_makarova
| 1 |
We have corrected as recommended. Table 4 sent to supplementary material as supplementary table 3.
| 2 | 1 |
P12 L283: Is Table 4 necessary? The title (and aim?) of the paper is all about comparing techniques against the 4C model. One also begins to wonder about affecting type 1 errors due to multiplicity of comparisons (debatable but worth considering). It may be worth considering moving Table 4 to the supplementary file and bringing supplementary Table 1 into the main document. If the focus (see the title) of the article is comparisons with the 4C model, then supplementary Table 1 seems to merit more direct attention.
| 1 | 2 |
nu14051073_makarova
| 1 |
Changed as supplementary figure 3.
| 2 | 1 |
As stated above, it may be worth considering moving these Bland-Altman figures to the supplementary file.
| 1 | 2 |
nu14051073_makarova
| 1 |
Changed, line 19 INTRODUCTION 3.
| 2 | 1 |
It should perhaps be the last paragraph in the Discussion. DISCUSSION P15 L393: This paragraph reads more like a conclusion and seem out of place.
| 1 | 2 |
nu14051073_makarova
| 1 |
We have stated in the conclusion that while individual methods show bias relative to the 4-component reference, the high correlations indicate that all the methods perform well in ranking individual children as having high or low FFM and fat mass. This ranking is itself very valuable in routine clinical care, particularly for longitudinal assessment. We have provided new evidence for the Mexican population that all the methods have utility for this purpose. Furthermore, some of the biases for individual methods can be resolved by the publication of method-specific reference data, whereby all data can be converted to method-specific z-scores. Publishing such reference data is a further aim of our project.
| 2 | 1 |
Much of the Discussion addresses strengths and weaknesses of the different BC methods, as if to provide guidance for clinicians in selecting the best techniques according to their needs and capabilities. None of the methods are ideal – all are flawed (in comparison with a gold standard). Yet a firm conclusion seems to be lacking. Concluding that methods differ is not surprising. One may be better served by discussing how the differences in methods (i.e. over or under estimating FM) may affect health assessments. That is, what impact may underestimating FM, by relying on one particular method, have on child care? How critical is the method selection? Somehow this needs to be tied more firmly to the population and environment being studied.
| 1 | 2 |
nu14051073_makarova
| 1 |
added
| 2 | 1 |
I am not familiar with the Bland-Altman method, so was unclear when I read the methods section whether the text in lines 204-207 was explaining the Bland-Altman method or describing a separate procedure. I take from the results that those sentences were describing the Bland-Altman procedure, and if so, adding some text along the lines of "In this procedure..." would be helpful. As it was, I couldn't understand the description provided, and it didn't seem to match the figures, which were simply labeled as FM, so seemed to be a simple plots of FM using 2 methods on first read.
| 1 | 2 |
nu14051073_makarova
| 1 |
Added to supplementary figure 1 and main figures 1 and 2 3.
| 2 | 1 |
Relatedly, it would have been helpful to have more explanatory titles for the plots--eg "Differential correlation between methods across levels of FM". And, the meaning of the trend line was very counter-intuitive, so an interpretive note under the plots would have been helpful. (E.g., "A positive trend indicates increasing underestimation of FM at high FM levels; a negative trend indicates increasing overestimation of FM at high FM levels.
| 1 | 2 |
nu14051073_makarova
| 1 |
Specified in limitations lines 993-997. Important to say is that ~89% of Mexican population is Hispanic. Only 6.6% belong to indigenous population and 5.9% to Afro-Mexican ethnic groups.
| 2 | 1 |
There is no description of the race and ethnic composition of the sample. I am not well-versed in the ethnic composition of Mexico, however, would it be helpful to know the degree of representation of, for example, youth who are Black, of Indigenous ancestry, and of European ancestry? Or are there other ethnic or cultural groups that should be represented?
| 1 | 2 |
nu14051073_makarova
| 1 |
Corrected. In the previous version we put data of the whole sample of 293 subjects (including 5 outliers that should not been there). We have corrected the data, and now we only present data on the 288 subjects for both tables.
| 2 | 1 |
I didn't understand why the data differed between Table 1 and Supplementary Table 1. Why did Ns (and means/SDs) differ?
| 1 | 2 |
nu14051073_makarova
| 1 |
Added to table 1.
| 2 | 1 |
Not all abbreviations are listed for the table footnotes (FFM, D2O, DXA, LM, BV, ADP)
| 1 | 2 |
nu14051073_makarova
| 1 |
Thank you for your comment, we have tried to make the abstract less fragmented -Theoretical framework: it is very updated.
| 2 | 1 |
Abstract: it is not conventional. It is very “fragmented”. Try to elaborate it again.
| 1 | 2 |
nu14122489_perova
| 1 |
Thanks for your comments, we have found a more updated reference (reference 18), cited in lines 96-98 to explain more the importance of HRQoL.
| 2 | 1 |
Theoretical framework: it is very updated. To be prudent, try to update some references if you find.
| 1 | 2 |
nu14122489_perova
| 1 |
Line 501-503 We have added that we used a large sample size and that this was powerful enough to detect significant differences within sub-groups. We have also added a further description of our ability to capture results in a snapshot of time. I hope this clarifies this aspect.
| 2 | 1 |
Methods. This paper is based on cross sectional method. Can you justify it in depth? This study includes a size of 1139 adolescents.
| 1 | 2 |
nu14122489_perova
| 1 |
Thank you for your comment, the updated figures and tables are now at the end of the paper.
| 2 | 1 |
Results. In Results, the separations of text and Figures and Tables is strange (when a paper does it, the trend is to include it at the end of all the paper). I recommend you to alternate them (text, Figures and Tables in Results). Nevertheless, results are well elaborated.
| 1 | 2 |
nu14122489_perova
| 1 |
Thank you for your comment, we are glad that you think so
| 2 | 1 |
Conclusion and discussion: They are well elaborated.
| 1 | 2 |
nu14122489_perova
| 1 |
Thank you for your comments about the instruments and the associated domains. We have updated these and aimed to explain them in more detail and with more clarity, sections 2.5, 2.6 and 2.7 lines 193-196, 215-225, 236-244.
| 2 | 1 |
The level of reporting of the core assessment instruments and their items, dimensions and subdomains needs to be enhanced.
| 1 | 2 |
nu14122489_perova
| 1 |
These issues have been addressed. The tables and figures are more clear and more detailed. We have provided are reasoning for the choices of statistical methods.
| 2 | 1 |
There is a need to revising the reporting of the results and information in the tables along with the statistical methodology used with interval data and group comparison research.
| 1 | 2 |
nu14122489_perova
| 1 |
Thank you for this concern. We have aimed to explain that the KS-10 takes items from the longer KS versions but does not measure for each dimension as it is a general score. However, you have made a great point that some associations may be lost on the specific dimensions, we have tried to explain this reasoning such the burden of participation is lower to complete the KS-10 version lines 493-494 . We wanted to use the general score so that results can be compared with other studies and in other countries, which is one of the advantages of KS-10. Thank you for the insight, this has made us reflect on the KS-10 from the longer versions more.
| 2 | 1 |
The focus on only the global mean score for the wellness KQ-10 measure rather than the 5 dimensions. Diet is only expected to influence 2 of these 5 dimensions.
| 1 | 2 |
nu14122489_perova
| 1 |
We have now recognised the impact and importance of income to a greater depth and are thankful for your comments on this matter. It is a shame that we cannot say anything about income in this article as this was not measured, only parental education, however this has been suggested for future studies lines 535-537 .
| 2 | 1 |
The lack of recognition that income and cost of living rather than education of parents is also a likely reason for the findings.
| 1 | 2 |
nu14122489_perova
| 1 |
We have now made a recommendation to investigate this in more depth and to compare diet quality between school time and home time. It is important to assess if the lunches are the same across students of different SES, some insight on this is given in lines 522 and 534 and that an issue could be the diet quality provided at home as school lunches may even-out diet-related inequalities. Thank you for the recommendation as this is an important aspect of adolescents’ diet.
| 2 | 1 |
The lack of recommendations associated with the Swedish free lunch program to assist the diets of students in low SES families to have more fruit and vegetables
| 1 | 2 |
nu14122489_perova
| 1 |
Thank you for your comments on this matter, we have edited this and hope it makes more sense now and that it does not make that assumption any longer, see lines 48-50.
| 2 | 1 |
The first sentence assumes that poor diet is always associated with adolescents, this is incorrect Better to say: Adolescents often do not consume a high-quality diet, concurrently their self- 13 reported mental health problems are increasing.
| 1 | 2 |
nu14122489_perova
| 1 |
We understand your concern, there are a lot of abbreviations, the abbreviations have been re-written in each section to help follow the flow, and we have now added an abbreviation and key word table before the introduction to provide additional help for readers, thank you for this comment lines 37-45.
| 2 | 1 |
Line 90 need to put in the full name Health Related Quality of Life (HRQoL). You have so many abbreviations confusing to follow in places. The authors may know what these are, but many reader will not. To assist the reader’s comprehension, explain the instruments more as you develop the paper.
| 1 | 2 |
nu14122489_perova
| 1 |
Thank you for your great comment, we want the dimensions to be clear for the readers and this is an important observation. We have now edited how the SHEIA and RADDS variables are explained as well as the KS-10, sections 2.5 and 2.6 and we hope they are clearer to understand lines 193-196, 215-225, 236-244.
| 2 | 1 |
The important issue is in the method section the reader needs understand the dimensions and sub-dimension that make up within each survey. Unless these are included the reader can not fully understand the study.
| 1 | 2 |
nu14122489_perova
| 1 |
Thank you for your comments, it is important to mention status and the term SES-F has now been incorporated. We have also now used the term parental education and in section 2.7 we have mentioned that this was used as a proxy for SES, lines 257-258. This is to make it clearer that we only had access to parental education and no other SES-Fs and we hope that this is clearer now, we have used parental education instead of SES in lines 21, 111-114 and 149-150. We have also emphasised the importance of parental income, lines 419-428, 503-506, 533-537 and 550-555.
| 2 | 1 |
The term is usually SES social economic status so it should be SES- F if it is social economic status – factors. Given you are using education of parents as the status measure of SES the term status is important in this paper and should not be dropped.
| 1 | 2 |
nu14122489_perova
| 1 |
Thank you, we agree that income as well as education plays a role in healthy food choices. However, the results in the article we are referring to looked at parental education, not income. As we did not have access to data in parental income, we were not able to include that variable in our paper
| 2 | 1 |
It is more that education it is also income re line 106-107 “It is proposed that parents with more educational experience are more likely to make healthier food choices for their family” . Miss the point It also assumes that parents with more educational experience are more likely to have higher incomes and so are more likely to make and avoid healthier food choices for their family
| 1 | 2 |
nu14122489_perova
| 1 |
Although a higher education might lead to a higher income we unfortunately do not have the data to look at that but as previously mentioned we have now stressed the importance of parental income, lines 419-428, 503-506, 533-537 and 550-555, thank you for pointing this out.
| 2 | 1 |
It also assumes that parents with more educational experience are more likely to have higher incomes and so are more likely to make and avoid healthier food choices for their family.
| 1 | 2 |
nu14122489_perova
| 1 |
Thank you for your comment, income is most certainly important and we have now emphasised its importance in lines 419-428, 503-506, 533-537 and 550-555. We also have mentioned that parental education is being used as a proxy for SES lines 257-258 but we cannot infer anything about income as this was not measured, only parental education, not overall SES.
| 2 | 1 |
If income is not important than the paper should be the on home education level and home diet not home SES and home diet.
| 1 | 2 |
nu14122489_perova
| 1 |
Thank you for suggesting that we reference these two papers, Darmon and Drewnoski was very insightful and most certainly useful for this article, and we now make it clearer that education is a factor of SES and a proxy for income. Lines 419-428 offer an insight into income and affluence, however we have elaborated more on income in future perspectives 533-537 and in the conclusion, lines 550-555 as it may, as you say, play a significant role in these associations.
| 2 | 1 |
See Murayama, N. (2015). Effects of socioeconomic status on nutrition in Asia and future nutrition policy studies. Journal of nutritional science and vitaminology, 61(Supplement), S66-S68. Darmon, N., & Drewnowski, A. (2008). Does social class predict diet quality?. The American journal of clinical nutrition, 87(5), 1107-1117. The issues raised in the well quoted Darmon and Drewnowski paper need to be considered more.
| 1 | 2 |
nu14122489_perova
| 1 |
Thank you for your comment, we want to make the definition of this index as clear as possible and we have edited this in section 2.5.1 and included the sub-components, lines 193-196. We have also cited that reference in both sections 2.5.1 and 2.5.2 so that readers can find a more detailed description. We have also edited section 2.5.2, lines 215-225 so that the RADDS index is also easier to understand and have mentioned some of the sub-components.
| 2 | 1 |
The Swedish Healthy Eating Index for Adolescents 2015 (SHEIA15) is not well explained in this paper. The following paper did a better job of reporting it Moraeus L, Lindroos AK, Warensjö Lemming E, Mattisson I. Diet diversity score and healthy eating index in relation to diet quality and socio-demographic factors: results from a cross-sectional national dietary survey of Swedish adolescents. Public Health Nutr. 2020 Jul;23(10):1754-1765. doi: See their Table 5.
| 1 | 2 |
nu14122489_perova
| 1 |
Thanks for your observation, we have now tried to describe the KS-10 with more details, and to make it clearer, section 2.6, 236-244.
| 2 | 1 |
The KIDSCREEN-10 is not well described. The basic information is not there in the paper: “KIDSCREEN-10 (KS-10) is derived from the KIDSCREEN-27, and provides a single index of global QoL using ten items related to physical well-being, psychological well-being, autonomy and parent relation, social support and peers, and school environment” See how these researchers have described the KIDSCREEN-10 . Bouwmans, C., van der Kolk, A., Oppe, M., Schawo, S., Stolk, E., van Agthoven, M., ... & van Roijen, L. (2014). Validity and responsiveness of the EQ-5D and the KIDSCREEN-10 in children with ADHD. The European Journal of Health Economics, 15(9), 967-977.
| 1 | 2 |
nu14122489_perova
| 1 |
We are very pleased that you found this interesting!
| 2 | 1 |
In terms of results the flowchart was interesting.
| 1 | 2 |
nu14122489_perova
| 1 |
Thank you for this comment, the figure may have been minimised and red meat and poultry are now visible which may not have been before, apologies for this, also we have mentioned some of the sub-components in lines 215-225. Also the figures and tables became distorted when the manuscript was uploaded, we have fixed this.
| 2 | 1 |
I am a not European reviewer and so found the RADDS a rather restricted list without some meat.
| 1 | 2 |
nu14122489_perova
| 1 |
Thank you for your comment. However, we think chi-squared is the appropriate statistical test as we are only comparing the proportions of distribution between categorical variables, we are not comparing the means between more than two groups which is what ANOVA is used for. We have not used chi square to assess analysis of variance, we have now made it clearer that frequency distribution is being assessed in the statistical methods section In terms of gender and education: the mean, standard deviation, df and sig t or F test need to be reported in the tables.
| 2 | 1 |
Why was the Pearson's chi-squared test used (table 1) for analysis of variance? For while gender and in this study education are categorical (group) the data being evaluated is continuous and interval data and so an ANOVA or MANOVA by group is the method of analysis of variance. (Tabachnick, B.G., Fidell, L. S., & Ullman, J.B. (2007). Using multivariate statistics (5th ed.). Pearson.)
| 1 | 2 |
nu14122489_perova
| 1 |
Thanks for this comment, we have incorporated t and df scores, see tables 1 and 4.
| 2 | 1 |
In terms of gender and education: the mean, standard deviation, df and sig t or F test need to be reported in the tables.
| 1 | 2 |
nu14122489_perova
| 1 |
This has been put in the appendix, table A1, page 18, thanks for the suggestion The regression analyses “p” value is reported, but the beta values and significance must also be reported.
| 2 | 1 |
Similarly, a correlation matrix is typically reported as it the foundation of regression analyses and so it needs to be reported to understanding the interaction between three main tests variables being investigated in this study.
| 1 | 2 |
nu14122489_perova
| 1 |
Great that you mentioned the beta values, the coefficients in the tables are in fact unstandardised beta coefficient values, this has been made clearer in the tables. The tables have diet (ind variable) on the left and the dependent variable KS-10 is on the top to indicate that interaction, then this is stratified by gender. I hope this makes more sense now.
| 2 | 1 |
The regression analyses “p” value is reported, but the beta values and significance must also be reported. The regressing table needs reworked, as it is the influence of diet the independent variable on wellbeing KO-10, the dependent variable. If the focus is on gender typically both a boy and a girl regression model is reported.
| 1 | 2 |
nu14122489_perova
| 1 |
We had a problem with uploading the figures and they became distorted, thank you for your comments, we have fixed this and incorporated t and df values.
| 2 | 1 |
Table 5 is interesting but the setting out is poor and so the columns do not align with headings, particularly the wellness KQ -10 information. Again, an ANOVA “ t” value and df as well as the p value have to be reported. In table 5 only one p value is reported, but what it is measuring is unclear, as there are a number of interactions occurring. Should be reporting total, then girls, and then boys as there look to be interaction effects.
| 1 | 2 |
nu14122489_perova
| 1 |
We appreciate your concern regarding the KS-10 item domains. The reason we chose to use the general item value is that it is less burdensome than the longer versions and it is best practice to use the general score and not to directly try to analyse for each dimension. We are not sure that it is a fact that diet can not influence parent relations or social relations, if diet can help to improve quality of life then this may improve how an adolescent feels and their emotions which ultimately may have an influence on relations to others. However, we realise that we may miss out other findings and have mentioned this as a limitation, lines 496-497 and we appreciate your views on this matter. We have also incorporated more information about KS-10 reliability in measuring HRQoL, 236-244This is also a cross sectional study and so only associations can be established not causations.
| 2 | 1 |
Because the KQ-10 is a composite tests there is the likelihood to be some interaction with the sub-domains. Focusing only on the global KQ-10 scores is hiding the subdomain differences to diet. Diet is not expected to have any influence of parent relations, social relations or peers but your study may find an influence on psychological well-being and even school environment. This is the core of your study: does diet have an influence on psychological wellbeing? Remember the KQ-10 is made up of five subdomains (psychological well-being, autonomy and parent relation, social support and peers, and school environment) The fact is diet is no expected to change 3 of these KQ-3 subdomains and only one or two KQ-10 dimensions. Use all five of the KO-10 dimensions as your outcome measure not the Mean average global KQ-10 score. You may have a more important study if you do that, with a different finding to what you have just using the composite total.
| 1 | 2 |
nu14122489_perova
| 1 |
Great comments, we have elaborated more on income, lines 419-428, 503-506, 533-537 and 550-555. We have also included a detailed section about the significance of school lunches and education in Sweden across different SES groups lines 528-532. In Sweden the school lunch is of rather high diet quality, reaching many of the national dietary recommendations and is provided free of charge regardless of income or SES. However, it would be insightful to a complete a deeper analysis investigating the differences of school quality across differing socio-demographic areas. Nonetheless, the problem related to diet quality may lie in the food provided at home as financial constraints are most likely to be of more significance, lines 528-534.
| 2 | 1 |
The conclusion is sound given the findings but the lack of reference to income is an issue as educational status of parents is often a “de-facto” measure for income. It maybe, it is the cost of living associated with fresh fruit and vegetables that is the real issue. Given the findings the researchers could be arguing that a review may be needed with the Swedish school lunch program and increase the level of fruit and vegetables in the students' diet, particularly for students in lower SES locations. Schools may be making the lunches to a budget rather than to a healthy diet criteria which is more expensive. Different sub-populations even in the same school may need different mix of foods. A public education program could also be encouraged about health eating.
| 1 | 2 |
nu14122489_perova
| 1 |
No comments to address (‘Yes’ ticked for all assessment criteria). We thank Reviewer 1 for their encouraging feedback.
| 2 | 1 |
The manuscript by Grant el al., is an interesting study in which they exhaustively utilized a very large database generated for almost 3 decades to analyze the representation of obesity and public health policy and its association with gender, healthiness, social status, and negative stereotypes by using machine learning and computational language analysis approach. This study highlights a very relevant topic of obesity and weight stigma in the society, particularly when the research have shown that “metabolically obese normal weight” people still exhibit significant risk of developing cardiovascular and other metabolic related disorders, regardless of having normal weight and BMI. This study deals with question that needs important discussion for obesity-related public health policy development.
| 1 | 2 |
obesities2010010_makarova
| 1 |
Thank you for your encouraging feedback on the potential reach of the findings. We have added at statement to this effect in the Discussion: Although based on a restricted area of exploration, Australian print news media only, our findings may have much broader significance for worldwide social trends and prompt the need for ongoing analysis of media reporting of obesity and weight-related public health policy. Future research could also extend our word embedding analysis to policy texts themselves, to draw direct correlations between media and policy data sources.
| 2 | 1 |
This is interesting topic that, although based on restricted area exploration, may have much broader significance in analyses that reveal worldwide social trends, as a whole.
| 1 | 2 |
obesities2010010_makarova
| 1 |
We agree that analysis of associations between weight-biased language in news media and the prevalence of eating disorders and other mental disorders correlated with weight stigma would be informative to the weight stigma literature, however our input data for the natural language processing (NLP) were textual data only and do not take into account other data modalities such as images and/or clinical data (floating numbers). In other words, NLP is a text-analytical tool to understand the nuances of human language about a certain topic (obesity in our case). This is done by capturing the contextual relationships between words and sentences in text corpus. Furthermore, this suggestion goes beyond the scope of the present paper, which focuses on associations between language biases tied to individual and structural dimensions of obesity and changes in public health policy rather than associations between language biases and changes in mental disorder prevalence. An alternative approach with the aid of NLP, would be to add mental disorders as a dimension in the analyses, but this would require a comprehensive literature review to make sure the mental disorder keywords, and their dichotomous mappings, were inclusive. Given the turnaround time for the revision (10 days), unfortunately we cannot extend the analysis in this way, but we absolutely agree with Reviewer 2 that this is an important and interesting direction for future research that can be achieved with further application of the techniques we have developed for this paper. We have acknowledged investigation of the association between news reporting on obesity and mental disorders as a fruitful direction for future research in the Discussion as follows: It is also important to examine relationships between news media reporting of obesity and health outcomes over time given, for example, medium to large meta-analytic associations between weight stigma and mental health disorders such as anxiety, depression, eating disorders and other psychopathological symptoms [new citation to be added and numbered accordingly – see below]. Emmer, C., Bosnjak, M., Mata, J. The association between weight stigma and mental health: A meta-analysis. Obesity Reviews 2020, 21:e12935. doi:10.1111/obr.12935 Comment 3:
| 2 | 1 |
I would like the authors to emphasize the impact of the analyzed trends by means of mental disorders, at least to those with significant clinical and medical importance. Therefore, I suggest exploring, using the same methodology, the data regarding the associations of weight-biased language with eating disorders (the incidence of anorexia nervosa and bulimia) and mood disorders (the incidence of depression and anxiety, etc.).
| 1 | 2 |
obesities2010010_makarova
| 1 |
We have provided new versions of the figure as a separate file to support editing/reproduction.
| 2 | 1 |
Legend for Figure 2 is missing.
| 1 | 2 |
obesities2010010_makarova
| 1 |
The research questions have been moved to the Introduction.
| 2 | 1 |
Please move the research questions from the methods to the introduction.
| 1 | 2 |
obesities2010010_makarova
| 1 |
This text was intended as an overview of what follows in the Results. We have moved it to the beginning of the Results and rephrased it as follows: In this section, we show the associations between obesity-related terms and the gender, healthiness, social status, and stereotype dimensions. These associations are subsequently cross-matched with the obesity policy timeline in the Discussion, to help interpret the context of change in biases over time.
| 2 | 1 |
Last paragraph of the methods: why did you report here your conclusions? Please move this part from this section.
| 1 | 2 |
obesities2010010_makarova
| 1 |
Figure 1 has been removed, along with the following associated text: Data extraction and analysis processes are illustrated in Figure 1.
| 2 | 1 |
Please revised Figure 1 because it's very difficult to read.
| 1 | 2 |
obesities2010010_makarova
| 1 |
We have added the following text from this paper in the first paragraph of the discussion as it seems to fit best with our results: Such entrenched weight biases, persistent in the media, may lead to internalised or self-stigma among individuals with overweight and obesity that persist even after weight loss. A recent study [insert numbered citation] performed a semantic evaluation of body shapes in obesity surgery patients and overweight/obesity controls and found that both groups were more willing to accept positive adjectives as a match when BMI was low and negative adjectives as a match when BMI was high.
| 2 | 1 |
I think this aspect is interesting and linked to your results, showing a connection with clinical data. A recent paper has pointed out that postbariatric patients, using a novel approach based on words, presented a weight bias regards their body, but it was not present for other bodies (see http://dx.doi.org/10.1007/s11695-020-05166-z).
| 1 | 2 |
obesities2010010_makarova
| 1 |
We have now added a Limitations and Future Research section to the Discussion to address this point and others: There are two limitations in our data curation process, the automated approach we used to check and select papers. Firstly, automatic classifiers of any sort can include some irrelevant or false positive articles. Due to the large amount of articles in our dataset, in Step 2 of our methodology, we developed a machine learning binary classifier – a support vector machine - with 87.56% accuracy to automatically identify relevant articles (accuracy is the number of correct predictions made, divided by the total number of predictions made, and then multiplied by 100 to convert it into a percentage). As a rule of thumb, accuracy of a predictive model that is above 80% is very commonly used to summarise the performance of that model. Still, it doesn’t exclude the possibility of irrelevant articles in our final dataset, but that possibility is less than 12.44 percent and this has to be considered against the benefit of scale and efficiency that this method allows. We also acknowledge that our analysis limited is in not being able to consider visual content visual content, images within articles (known as image framing), which have been shown to carry stigmatising elements [48]. This is something that could be added to the approach by including image classification along with additional measures. Furthermore, even though the Dow Jones is one the largest news databases, it might still miss some articles or news sources (although this doesn’t relate to the automatic approach as such). This applies to social media, even though this would not span as long a timeframe.
| 2 | 1 |
You report that an automatic approach was used to check all the papers. Is there any possible limit with this approach in the selection of the papers?
| 1 | 2 |
obesities2010010_makarova
| 1 |
No comments to address (‘Yes’ ticked for all assessment criteria). We thank Reviewer 1 for their encouraging feedback.
| 2 | 1 |
The manuscript by Grant el al., is an interesting study in which they exhaustively utilized a very large database generated for almost 3 decades to analyze the representation of obesity and public health policy and its association with gender, healthiness, social status, and negative stereotypes by using machine learning and computational language analysis approach. This study highlights a very relevant topic of obesity and weight stigma in the society, particularly when the research have shown that “metabolically obese normal weight” people still exhibit significant risk of developing cardiovascular and other metabolic related disorders, regardless of having normal weight and BMI. This study deals with question that needs important discussion for obesity-related public health policy development.
| 1 | 2 |
obesities2010010_perova
| 1 |
Thank you for your encouraging feedback on the potential reach of the findings. We have added at statement to this effect in the Discussion: Although based on a restricted area of exploration, Australian print news media only, our findings may have much broader significance for worldwide social trends and prompt the need for ongoing analysis of media reporting of obesity and weight-related public health policy. Future research could also extend our word embedding analysis to policy texts themselves, to draw direct correlations between media and policy data sources.
| 2 | 1 |
This is interesting topic that, although based on restricted area exploration, may have much broader significance in analyses that reveal worldwide social trends, as a whole.
| 1 | 2 |
obesities2010010_perova
| 1 |
We agree that analysis of associations between weight-biased language in news media and the prevalence of eating disorders and other mental disorders correlated with weight stigma would be informative to the weight stigma literature, however our input data for the natural language processing (NLP) were textual data only and do not take into account other data modalities such as images and/or clinical data (floating numbers). In other words, NLP is a text-analytical tool to understand the nuances of human language about a certain topic (obesity in our case). This is done by capturing the contextual relationships between words and sentences in text corpus. Furthermore, this suggestion goes beyond the scope of the present paper, which focuses on associations between language biases tied to individual and structural dimensions of obesity and changes in public health policy rather than associations between language biases and changes in mental disorder prevalence. An alternative approach with the aid of NLP, would be to add mental disorders as a dimension in the analyses, but this would require a comprehensive literature review to make sure the mental disorder keywords, and their dichotomous mappings, were inclusive. Given the turnaround time for the revision (10 days), unfortunately we cannot extend the analysis in this way, but we absolutely agree with Reviewer 2 that this is an important and interesting direction for future research that can be achieved with further application of the techniques we have developed for this paper. We have acknowledged investigation of the association between news reporting on obesity and mental disorders as a fruitful direction for future research in the Discussion as follows: It is also important to examine relationships between news media reporting of obesity and health outcomes over time given, for example, medium to large meta-analytic associations between weight stigma and mental health disorders such as anxiety, depression, eating disorders and other psychopathological symptoms [new citation to be added and numbered accordingly – see below]. Emmer, C., Bosnjak, M., Mata, J. The association between weight stigma and mental health: A meta-analysis. Obesity Reviews 2020, 21:e12935. doi:10.1111/obr.12935 Comment 3:
| 2 | 1 |
I would like the authors to emphasize the impact of the analyzed trends by means of mental disorders, at least to those with significant clinical and medical importance. Therefore, I suggest exploring, using the same methodology, the data regarding the associations of weight-biased language with eating disorders (the incidence of anorexia nervosa and bulimia) and mood disorders (the incidence of depression and anxiety, etc.).
| 1 | 2 |
obesities2010010_perova
| 1 |
We have provided new versions of the figure as a separate file to support editing/reproduction.
| 2 | 1 |
Legend for Figure 2 is missing.
| 1 | 2 |
obesities2010010_perova
| 1 |
The research questions have been moved to the Introduction.
| 2 | 1 |
Please move the research questions from the methods to the introduction.
| 1 | 2 |
obesities2010010_perova
| 1 |
This text was intended as an overview of what follows in the Results. We have moved it to the beginning of the Results and rephrased it as follows: In this section, we show the associations between obesity-related terms and the gender, healthiness, social status, and stereotype dimensions. These associations are subsequently cross-matched with the obesity policy timeline in the Discussion, to help interpret the context of change in biases over time.
| 2 | 1 |
Last paragraph of the methods: why did you report here your conclusions? Please move this part from this section.
| 1 | 2 |
obesities2010010_perova
| 1 |
Figure 1 has been removed, along with the following associated text: Data extraction and analysis processes are illustrated in Figure 1.
| 2 | 1 |
Please revise Figure 1 because it's very difficult to read.
| 1 | 2 |
obesities2010010_perova
| 1 |
We have added the following text from this paper in the first paragraph of the discussion as it seems to fit best with our results: Such entrenched weight biases, persistent in the media, may lead to internalised or self-stigma among individuals with overweight and obesity that persist even after weight loss. A recent study [insert numbered citation] performed a semantic evaluation of body shapes in obesity surgery patients and overweight/obesity controls and found that both groups were more willing to accept positive adjectives as a match when BMI was low and negative adjectives as a match when BMI was high.
| 2 | 1 |
A recent paper has pointed out that post-bariatric patients, using a novel approach based on words, presented a weight bias regards their body, but it was not present for other bodies (see http://dx.doi.org/10.1007/s11695-020-05166-z). I think this aspect is interesting and linked to your results, showing a connection with clinical data.
| 1 | 2 |
obesities2010010_perova
| 1 |
We have now added a Limitations and Future Research section to the Discussion to address this point and others: There are two limitations in our data curation process, the automated approach we used to check and select papers. Firstly, automatic classifiers of any sort can include some irrelevant or false positive articles. Due to the large amount of articles in our dataset, in Step 2 of our methodology, we developed a machine learning binary classifier – a support vector machine - with 87.56% accuracy to automatically identify relevant articles (accuracy is the number of correct predictions made, divided by the total number of predictions made, and then multiplied by 100 to convert it into a percentage). As a rule of thumb, accuracy of a predictive model that is above 80% is very commonly used to summarise the performance of that model. Still, it doesn’t exclude the possibility of irrelevant articles in our final dataset, but that possibility is less than 12.44 percent and this has to be considered against the benefit of scale and efficiency that this method allows. We also acknowledge that our analysis limited is in not being able to consider visual content visual content, images within articles (known as image framing), which have been shown to carry stigmatising elements [48]. This is something that could be added to the approach by including image classification along with additional measures. Furthermore, even though the Dow Jones is one the largest news databases, it might still miss some articles or news sources (although this doesn’t relate to the automatic approach as such). This applies to social media, even though this would not span as long a timeframe.
| 2 | 1 |
You report that an automatic approach was used to check all the papers. Is there any possible limit with this approach in the selection of the papers?
| 1 | 2 |
obesities2010010_perova
| 1 |
Figures have been revised with addition of arrows and text to represent the data. Since a large number of ILs were screened, susceptible check (SC) was used with a set of ILs and hence SC couldn’t be shown in all figures. However, SC ‘HR12’ for blast disease was shown in all blast screening figures 3 to 5. Similarly, in Fig 5, ‘TN1’ and ‘Improved Samba Mahsuri’ as susceptible and resistant checks respectively for BB in comparison with IL-19031 were shown. Authors once again thank the reviewer for pointing out the mistake in legends. Now, we have rephrased the legends clearly describing all the terms.
| 2 | 1 |
The main issue with the ms is the quality of the figures: they are not clearly representing the data, arrows and text may help the reader, the controls are missing in most cases, and a general lack of precision is affecting them. Also, the legends are not clearly describing all the terms and should be revised. Legends should describe what is to be observed in the figure, possibly pointing to parts of special interest.
| 1 | 2 |
plants11050622_makarova
| 1 |
Figure 1 legend has been revised with inclusion of the details of kharif and rabi seasons. kharif is the wet season with crop growing period from June to November and rabi is the dry season with crop growing period from December to May. We described kharif as wet season and rabi as dry season in the materials and methods section also.
| 2 | 1 |
Explaining briefly which and what are the indian sesasons during which experiments have been conducted would help clarity.
| 1 | 2 |
plants11050622_makarova
| 1 |
Since the number of ILs is large, presenting phenotypic data for each IL will result in increasing the size of the main tables, hence data was earlier presented in supplementary tables. As suggested by the reviewers, we have revised the tables and presented the mean phenotypic data of BB, blast and drought screening in the main tables for each IL in parenthesis. Column on ‘no. of genes/QTL’ has been removed as suggested. Entry nos have been replaced with IL No as suggested.
| 2 | 1 |
The phenotypic data are important, but currently they are presented only as additional material. The authors should consider reshaping the tables, eliminating unnecessary columns (e.g. no. of genes / QTLs, which is already represented in column 1) and add the most striking phenotypic data, when possible and relevant for discussion. Also "entry nos." is probably not clear and ILs no should maybe considered instead.
| 1 | 2 |
plants11050622_makarova
| 1 |
The present work is not essentially a backcross breeding program aimed at development of near isogenic lines. However, Krishna Hamsa was the common background into which several genes/QTL were targeted from multiple donors and considering the morphological similarity between 27 ILs and Krishna Hamsa, background selection was done retrospectively. BGS validated our observations on morphological similarity. The same has been discussed in the 5th para under ‘discussion’. Also results on BGS have been presented under subsection 2.3 of results with data on polymorphic markers for BGS in supplementary table S8.
| 2 | 1 |
The data on bgs are not sufficiently presented in the text nor discussed.
| 1 | 2 |
plants11050622_makarova
| 1 |
“()” have been removed while mentioned the numbers of the ILs and sentences have been revised appropriately in the manuscript.
| 2 | 1 |
revise the use of "-" instead of "( )" when mentioning the numbers of the ILs, or any other system which would ensure a better homogeneity in comparison to the one present in the ms.
| 1 | 2 |
plants11050622_makarova
| 1 |
The above mentioned lines have been checked and found either spelling mistakes or revision of sentences. Accordingly, corrections were made.
| 2 | 1 |
check lines 21, 37, 93, 153, 183-184, 312, 351-353, 360, 377, 466
| 1 | 2 |
plants11050622_makarova
| 1 |
BLB has been replaced with BB throughout the manuscript.
| 2 | 1 |
stick to BB instead of BLB
| 1 | 2 |
plants11050622_makarova
| 1 |
Legends of figures and tables and text in the results section have been revised with explanation of acronyms as suggested.
| 2 | 1 |
consider anticipating the explanation of the acronyms which are eventually presented only in the M&M, to facilitate the reading; consider this aspect also in the legends
| 1 | 2 |
plants11050622_makarova
| 1 |
The sentence here is required to maintain flow of the subsequent content.
| 2 | 1 |
Lines 403 et seq. are redundant Response:
| 1 | 2 |
plants11050622_makarova
| 1 |
Both lines explain our observations in different sets of ILs. Sentence at 351 explains susceptibility in ILs despite possessing the targeted gene/QTLs while sentence at 414 explains resistance in ILs despite the absence of targeted gene/QTLs.
| 2 | 1 |
lines 414 et seq. seem to be contradicting lines 351 et seq.
| 1 | 2 |
plants11050622_makarova
| 1 |
The 85 ILs is a sum total of nine ILs marker positive to blast- R genes, nine ILs harbouring QTLs for drought tolerance and 67 ILs marker positive to BB-R genes mentioned at the beginning of 4th paragraph of discussion. As suggested, we have added in brief about the same at line 414.
| 2 | 1 |
the 85 ILs presented at 414 seem to be a bit out of the blue: a short intro to where they are coming from would help the reader.
| 1 | 2 |
plants11050622_makarova
| 1 |
Authors profusely thank the reviewer for the appreciation.
| 2 | 1 |
Thank you for inviting me to review this manuscript. The paper itself is well written, although 1) somewhat results are partially descriptive and partially inferential. However, the authors have conducted a thorough literature review, undertaken a rigorous piece of data collection, and have generalized information accurately.
| 1 | 2 |
plants11050622_makarova
| 1 |
Yes, we agree that there were some typo and spelling mistakes in the manuscript. The manuscript has been thoroughly revised for the same.
| 2 | 1 |
With minor grammatical revisions, the manuscript can be accepted as is.
| 1 | 2 |
plants11050622_makarova
| 1 |
Authors feel greatly encouraged and motivated with the reviewer’s comments.
| 2 | 1 |
It is also acknowledged that this paper is probably the first of many papers to emerge from the study. As such, it is an overview paper that raises many questions. It would be interesting for the authors to provide more information about the research design and estimation methodologies, such as chi-square analysis of introgression lines, if possible for each crossed IL population. I only recommend some minor revisions before acceptance. Response: Authors once again thank the reviewer for correct assessment of the basic purpose of the manuscript. Yes, this is truly an overview paper presenting the interesting observations from our study. The introgression scheme and phenotyping of various biotic traits and drought phenotyping have been described in detail under ‘Materials and Methods’ section. The metric data on yield traits was statistically analyzed and results of ANOVA, heritability and critical differences have been presented in the manuscript. Authors agree that it would be more inferential with chi square values. However, the crossing scheme was viewed holistically and data on each cross was not maintained separately as the present study aimed at selecting introgression lines from multiples crosses with multiple stress resistance/tolerance by pooling several genes and QTLs into a common background. Despite maintaining large base populations, plants per se were selected based on marker positivity for inter-crossing and selfing and further stringent phenotypic selection for the targeted traits. Hence, chi-square which is perfectly apt for population derived from biparental crosses is not used in our study. This work is of outstanding quality, and I normally present more critical points in my reviews. However, this time it is just very beautiful work.
| 1 | 2 |
plants11050622_makarova
| 1 |
‘=261%’ has been corrected to ‘+261%’ and typo error of ‘linkes’ corrected to ‘linked’
| 2 | 1 |
Line 262: “=261 %” , and Line 312 “linkes” a typo? Correct it Response:
| 1 | 2 |
plants11050622_makarova
| 1 |
Thank you for the positive comments.
| 2 | 1 |
It was a pleasure to read this manuscript. I wish the author of the best.
| 1 | 2 |
plants11050622_makarova
| 1 |
We appreciate the suggestions from the reviewer, which has resulted in improving the message of the manuscript.
| 2 | 1 |
This paper described the multi-parents introgression assisted by molecular markers. The content is informative, however, the tables should be reorganized and the statistical methods description have to be improved. Please see the suggestion and comments below.
| 1 | 2 |
plants11050622_makarova
| 1 |
Added references appropriately at two places as suggested by the reviewer.
| 2 | 1 |
L48-63: should add some citations on the first part of introduction.
| 1 | 2 |
plants11050622_makarova
| 1 |
Explanation for boro season has been added.
| 2 | 1 |
L127: Please add the explanation of “boro season”.
| 1 | 2 |
plants11050622_makarova
| 1 |
Legends of the supplementary tables have been revised and inference of the table is given in foot note.
| 2 | 1 |
The legend of supplementary table should be improved. Table and main text are independent, so the authors have to describe the table more carefully.
| 1 | 2 |
plants11050622_makarova
| 1 |
Authors once again thank the reviewer for the valuable suggestion. More details on the statistical analysis have been added as suggested.
| 2 | 1 |
L562: the section of statistical analysis should add more details. Also please indicate the R version. For example, how does H2 calculate?
| 1 | 2 |
plants11050622_makarova
| 1 |
Yes, significant means p-value. In the supplementary tables, expanded form of DFF is given as suggested. Treatments refers to introgression lines and check to control. For uniformity, we have changed the terminology to treatment instead of using IL or variety and check to control in all the revised supplementary tables and rephrased the legends accordingly.
| 2 | 1 |
On Supplementary table S2, does significant mean p-value? Indicate DFF = days to fifty percent flowering. What is the “treatment”? What do the results on “check” mean? How did you analyze “control vs IL”?
| 1 | 2 |
plants11050622_makarova
| 1 |
Similar to Supplementary Table S2, S3 has been revised
| 2 | 1 |
On Supplementary table S3, similar questions as S2, please also explain.
| 1 | 2 |
plants11050622_makarova
| 1 |
CD is the critical difference at 1% and 5% level of significance (p-value) for testing of significant differences among the ILs. The details of CD calculation have been added in the materials and methods section as suggested.
| 2 | 1 |
On Supplementary table S5, what is “C.D”? How did you calculate those values on those comparison types?
| 1 | 2 |
plants11050622_makarova
| 1 |
Supplementary table S5 is on CD and corrections have been addressed as suggested as at S. No 7. Supplementary table S6 have been modified by shifting data of BB and blast scores to main table. Each PC group is mentioned on top as sub heading at the start of each group. Each IL is presented only once in the entire table under separate PC groups.
| 2 | 1 |
Please re-organize the Supplementary table S5, I suggest use each ILs only appear one time and add one more column to show their PC groups. Then the table can be more informative and ease to read.
| 1 | 2 |
plants11050622_makarova
| 1 |
Full names of the abbreviations have been added as suggested.
| 2 | 1 |
Please add the full name of abbreviations. For example on L203 “CD”, L211 “SES“, L228 “UBN“ and L332 “ICAR-IRRR”.
| 1 | 2 |
plants11050622_makarova
| 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.