Update README

README.md

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 ---
-license: apache-2.0
+license: odc-by
+language:
+  - en
+task_categories:
+  - text-generation
+size_categories:
+  - 1B<n<10B
+tags:
+  - scientific
+  - pretraining
+  - web-corpus
+  - stem
+  - common-crawl
 ---
-Dataset Source: Randomly sampled from the original full dataset.
----
+
+# HW-Sci Sample (Anonymous Submission)
+
+This repository hosts a **representative sample** of the HW-Sci scientific
+web corpus, released anonymously for double-blind peer review at NeurIPS 2026.
+
+The full 1.09T-token corpus, finalised license, classifier checkpoints, and
+long-term maintenance repository will be released at the non-anonymous
+location at camera-ready time, pending internal release review.
+
+## Sample Composition
+
+The sample (~3.46 GB compressed) is uniformly distributed across all
+**14 STEM disciplines** covered by HW-Sci:
+
+AerospaceEngineering, Agriculture, Astronomy, Biology, Chemistry,
+CivilEngineering, ComputerScience, EarthScience,
+ElectricalElectronicEngineering, MaterialsScience, Mathematics,
+MechanicalEngineering, Medicine, Physics.
+
+Each discipline lives under its own top-level folder; documents are stored
+as gzip-compressed JSONL shards (`HainaWeb-Sci_<discipline>_<id>.jsonl.gz`).
+
+## Data Schema
+
+Each line is a JSON object. Refer to the paper's Appendix A (Datasheet) for
+the full field-level specification. Key fields:
+
+- `text`: main document text after the full curation pipeline.
+- `metadata`: original WARC fields (URI, content-type, crawl date, etc.).
+- `websci_meta.language`: detected language and confidence.
+- `websci_meta.discipline`: fine-grained discipline distribution from
+  the two-tier discipline router (top-4 disciplines with confidence).
+- `websci_meta.model_quality_score`: content-driven fastText quality score.
+- `websci_meta.sci_quality_score`: 0–5 scientific value score from the
+  rubric-based quality classifier.
+
+## Curation Summary
+
+Documents are sourced from Common Crawl snapshots (2013–March 2026) and
+DCLM-Pool, then processed by the data-centric curation pipeline described
+in Section 3 of the paper:
+
+1. Heuristic filtering with discipline-aware differential rules.
+2. Two-tier content-driven discipline routing.
+3. Rubric-based quality scoring with asymmetric penalties.
+4. Intra-dump fuzzy + intra-disciplinary exact deduplication.
+
+## PII Handling
+
+Personally identifiable information has been masked using the standard
+Datatrove PII formatter: email addresses are replaced with placeholders
+(`user@domain.org`); public IPs are replaced with the RFC 5737 TEST-NET
+address (`198.51.100.1`).
+
+## License
+
+This sample is released under the
+**Open Data Commons Attribution License (ODC-By) v1.0**.
+Use of the data is also subject to the original
+[Common Crawl terms of use](https://commoncrawl.org/terms-of-use).
+
+## Intended Use
+
+This anonymous sample is provided **solely for reviewer evaluation** of the
+NeurIPS 2026 submission. Redistribution prior to camera-ready is not
+permitted. The full corpus, code, classifier checkpoints, and Datasheet
+will be released at the non-anonymous repository at camera-ready.
+
+## Limitations
+
+- English-only; humanities and social sciences are out of scope.
+- Code and multimodal content are not included.
+- Sample size is intentionally limited for reviewer inspection; quality
+  metrics reported in the paper are computed on the full corpus, not
+  this sample.
+
+## Reporting Issues
+
+Anonymous review channel — please contact the authors via the
+OpenReview submission discussion thread.