Update README.md

README.md

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   example_title: "Clinical Psychology Abstract 2"
 - text: " There is growing evidence of deficits in defensive reactivity (indexed by the startle blink reflex) in individuals diagnosed with antisocial personality disorder (ASPD). However, to date, no study has examined the role of defensive reactivity in the quality of life (QoL) of individuals with ASPD. In the current study, we therefore explored whether the startle blink reflex is negatively associated with QoL in 143 individuals diagnosed with ASPD. Defensive reactivity was measured using a fear-potentiated startle reflex test. To assess QoL, participants completed the Short Form (36) Health Survey (SF-36). Startle blink reflex potentiation deficits during aversive picture viewing were common in the sample (62.3%). Blink reflex potentiation was negatively and significantly associated with QoL. In sum, these findings provide clear evidence that deficits in defensive reactivity are linked to poor QoL in ASPD."
   example_title: "Clinical Psychology Abstract 3"
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+---
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+## Model
+SciBERT text classification model for positive and negative results prediction in scientific abstracts of clinical psychology and psychotherapy. 
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+## Data
+We annotated over 1,900 abstracts into two categories: 'positive results only' and 'mixed and negative results', and trained models using SciBERT.
+The SciBERT model was validated against one in-domain and two out-of-domain data sets comprising psychotherapy abstracts. We compared model performance with three benchmarks: natural language indicators of result types, *p*-values, and abstract length. Further information on documentation, code and data for the project "Publication Bias Research in Clincial Psychology Using Natural Language Processing" can be found on the Github repository [PubBiasDetect](https://github.com/PsyCapsLock/PubBiasDetect).
+
+## Using the Model on Huggingface
+The model can be used on Hugginface utilizing the "Hosted inference API" in the window on the right.
+Click 'Compute' to predict the class labels example abstract or an abstract inserted by yourself.
+The class label 'positive' corresponds to 'positive results only', while 'negative' represents 'mixed and negative results'.
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