Bibliographic record
Abstract
Toxicology has never been more important. Advances in chemistry and technology offering improvements in the quality of human life become ever more rapid, bringing with them the potential for new toxicity hazards. This has led to legislation requiring toxicity testing and risk assessment for all chemicals and their uses. The new REACH (Risk Evaluation and Authorization of Chemicals) Regulation has profound economic consequences because, without official authorization, a chemical cannot be marketed. This book explains, in depth, the ideas underlying current advances in toxicology and its application in regulating and ensuring the safe use of chemicals. Sometimes old ideas have become assumptions that have become embedded in related laws and regulation, even though the thinking of toxicologists has moved on in line with developments in science. This leads to confusion in public understanding that the book should dispel. There are also fundamental ideas in toxicology that are not well understood concerning the concepts of hazard and risk and even about what constitutes a chemical. For many people the word 'chemical' describes manmade substances only. In fact, it is correctly applied to all substances that exist, from pure elements to the most complex biological molecules in food and medicines. This is further complicated by the complex distinction between the descriptors, 'toxic' and 'nontoxic'. Developments in epigenetics are revolutionizing our understanding of mutagenicity and carcinogenicity. Improved understanding of apoptosis and necrosis leads to improved interpretation of potentially toxic effects at the cellular level. The recently defined term 'chemical speciation' is driving more targeted research on the toxicity of inorganic chemicals. This book explains the concepts implied by key toxicological terms using diagrams to illustrate the relationships between them. It is an essential aid to understanding the new demands from regulators of risk assessment and to the implementation of appropriate risk management.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.038 | 0.000 |
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 teacher head, 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".