S74 | REFTPS | Transformation Products and Reactions from Literature
Bibliographic record
Abstract
This is the collection associated with list S74 REFTPS Transformation Products and Reactions from Literature on the NORMAN Suspect List Exchange. https://www.norman-network.com/nds/SLE/ This dataset is designed to provide an entry point for users to contribute transformation products and reactions documented in the literature for addition to the NORMAN SLE, SusDat and the PubChem Transformations section. Change logs and version tracking at the ECI GitLab site. NOTE: This deposition is work in progress ... Change log: v0.0.2 added InChIKey file. v0.1.0 added new reactions from Anca Baesu and DTXSIDs. v0.2.0 added PFAS TPs from Parviel Chirsir. v0.2.1 more PFAS TPs from Parviel. v0.3.0 Emma added HMMM TPs; v0.3.1 updated references and added new CIDs; added new MS/MS file. v0.4.0 new PFAS TPs plus MS/MS and NMR. v0.4.1 new CID added, plus CID 67543 updated to 14571268.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.236 | 0.287 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".