Bibliographic record
Abstract
Received 14 January 2002; in final form 18 January 2002 Occupational hygienists and other health scientists should have little problem in accepting that approaches to the management of risk should be based on soundly constructed principles of risk assessment. Such thinking permeates many aspects of occupational health practice and is reflected in supporting legal frameworks, for example the Chemical Agents Directive (EC, 1998) and UK Control of Substances Hazardous to Health (COSHH) Regulations (Department of Health, 1999). Yet within Europe, such approaches are now under discussion concerning their relevance to other aspects of chemicals management. Three areas in the current debate are most pertinent.1. Despite the fact that Europe has in place an extensive regulatory system covering the marketing of chemicals, there remains a lack of information about their properties and uses. This, coupled with concerns over the effectiveness and efficiency of the system itself, has led the European Commission to reassess how the risks from chemicals ought best to be regulated in the market place. The Commission Strategy for a Future Chemicals Policy (European Commission, 2001b) outlines a basis for a new approach. The key feature of the proposal is a single system (termed ‘REACH’) where key information for most chemicals will be registered in a central database. The information requirements will vary, with higher levels being demanded when higher risks are likely. For some chemicals of very high concern (most probably established carcinogens, mutagens and reprotoxins), manufacturers of these substances will additionally be required to seek authorization for their continued use and to demonstrate that safer alternatives are not realistically usable.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.014 | 0.005 |
| Insufficient payload (model declined to judge) | 0.059 | 0.023 |
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".