Bibliographic record
Abstract
References to figures are given in italic type.References to tables are given in bold type.absorption 25 acceptable daily intake (ADI) 4-5 acceptable level of exposure 372-373 acceptance testing 468 accumulation 62-63 see also tissue concentration acetylcholinesterase (AChE) 137-139 AChE see acetylcholinesterase ACSLXtreme software 97-98 acute toxicity 299-300, 401 compound category formations 300-303 expert systems and 308-311 mammals 300-308 additivity 285-286 adduct formation, DNA 277 age 108 liver weight and 116-119 physiological data availability and 111-116 air quality modeling 449-451 Akaike information criterion (AIC) 386 alcohols 305-306 alkanes 304 anilines 306 APEX model 324-325 area under concentration-time profile (AUC) 401, 403 aryl hydrocarbon receptor (ACR) 167-168, 187 atmospheric flux 333 attractor states 182, 194 AUC (area under concentration-time profile) 401, 403 automatic differentiation 440 autoregulation motifs 188-194
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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.869 | 0.838 |
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".