Handbook of Toxicology and Ecotoxicology for the Pulp and Paper Industry
Bibliographic record
Abstract
Toxicology: Toxicity Acute studies Short-term (repeated dose) studies Long term studies Chemical Irritancy and Corrosive Effects: The skin The eye Respiratory irritation Chemical Allergies: The immune system Chemical hypersensitivity Contact hypersensitivity (allergic contact dermatitis) Respiratory hypersensitivity (Occupational asthma) How to test for allergic reactions Genetic Toxicology and Carcinogenicity: Mutagenicity Genetic toxicity testing Testing for chemical carcinogenicity Reproductive Toxicology: Reproductive toxicity testing Ecotoxicology: Aquatic toxicity testing Short term (acute) and long term (chronic) effects Test design Test species Vertebrates Invertebrates Aquatic plants Chemical Persistence and Bioaccumulation: Biodegradation BOD and COD tests Bioaccumulation Classification and Labelling of Chemicals According to Their Hazardous Nature: Europe, Canada USA Handling Chemicals in the Workplace: Risk assessment Chemical hazards Regulatory Affairs: Chemical inventories Food contact regulations Ecolabelling HPV programme Issues of concern The Material Safety Data Sheet: How to deal with toxicological or ecotoxicological data gaps Chemical summary sheets Glossary of terms
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.085 | 0.097 |
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".