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PLOS Cleaned JSONL Dataset — 50+ GB of Machine-Ready Scientific Text
This repository delivers a fully cleaned and standardized large-scale corpus extracted from the complete PLOS scientific archive, reorganized and formatted into high-quality JSONL files. All content is optimized for immediate use in modern LLM training pipelines (OpenAI, Mistral, DeepSeek, Llama, Gemma, etc.). Total size (compressed): ~50 GB • Articles processed: hundreds of thousands • Cleaning quality: ~98–99% • Format: JSON Lines (.jsonl)
Features
Full PLOS corpus reorganized by year: output/datasets_by_year/year_2003.jsonl → year_2025.jsonl
Train/val/test splits ready for training: output/splits/train.jsonl, val.jsonl, test.jsonl
Grouped by journal (all PLOS branches): Medicine, Genetics, Pathogens, Climate, Computational Biology, Digital Health, Global Public Health, ONE, Biology, Neglected Tropical Diseases, etc. Example: output/datasets_by_journal/PLOS_Medicine.jsonl, PLOS_Genetics.jsonl, PLoS_Biology.jsonl, PLOS_ONE.jsonl, etc.
JSONL Structure
Each line follows the same cleaned schema, ideal for training, RAG, or vector embedding:
{ "title": "Article title", "abstract": "Cleaned abstract...", "body_text": "Full cleaned article body...", "journal": "PLOS Medicine", "year": 2018, "authors": ["First Author", "Second Author"], "doi": "10.1371/journal.pmed.xxx", "keywords": ["biology", "health"], "clean_text": "Final merged cleaned text..." }
Cleaning Pipeline
Extraction from raw PLOS dumps
Multistage cleaning (regex, normalization, structure repair)
Removal of XML/HTML debris, broken text, figure callouts, corrupted sections
Unified schema + metadata alignment
Sorting by journal & by year
Automatic train/val/test splitting
Final QC ensuring no empty or malformed samples
Why This Dataset Matters
Massive 50+ GB scientific corpus ready for training
High-signal, peer-reviewed biomedical & scientific text
Perfect for:
biomedical/scientific LLM pretraining
SFT and supervised tasks
RAG systems & semantic search
reasoning models
dataset benchmarking
Fully stable, normalized, UTF-8 safe, consistent JSONL
License
PLOS articles are released under the PLOS Open Access license, which permits text mining, training, and research reuse.
Credits
Dataset extraction, cleaning, normalization, restructuring and validation carried out by Zeronex.
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