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index.html

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   </div>
 </section>
 
+  <section class="section">
+  <div class="container">
+    <h2 class="title is-3">📊 Results</h2>
+    <div class="highlight-box">
+      <p><strong>✔️ Accuracy</strong></p>
+      <ul>
+        <li>Spearman’s ρ > 0.87 with human ground truth</li>
+      </ul>
+    </div>
+    <div class="highlight-box">
+      <p><strong>📈 Downstream LLM Training Impact</strong></p>
+      <ul>
+        <li>+7.2% benchmark performance improvement</li>
+        <li>+4.8% token retention compared to FineWeb2 heuristic filter</li>
+        <li>Reliable thresholding with 0.6 and 0.7 quantiles</li>
+      </ul>
+    </div>
+    <div class="highlight-box">
+      <p><strong>⚡ Annotation Speed</strong></p>
+      <ul>
+        <li>~11,000 docs/min (on A100 GPU, avg. 690 tokens per doc)</li>
+      </ul>
+    </div>
+  </div>
+</section>
+
+<section class="section">
+  <div class="container">
+    <h2 class="title is-3">📁 Available Artifacts</h2>
+    <div class="highlight-box">
+      <ul>
+        <li>📄 Ground truth annotations in <strong>35 languages</strong></li>
+        <li>🧠 Synthetic LLM-annotated dataset (<strong>14M+ documents</strong>)</li>
+        <li>🪶 Lightweight annotation models:
+          <ul>
+            <li>JQL-Gemma</li>
+            <li>JQL-Mistral</li>
+            <li>JQL-Llama</li>
+          </ul>
+        </li>
+        <li>🛠️ Training & inference scripts <em>(coming soon)</em></li>
+      </ul>
+    </div>
+  </div>
+</section>
+  
 <section class="section">
   <div class="container content">
     <h2 class="title is-3">🧩 Main Pipeline Steps</h2>