Recording of Data of Individual Measurements of Occupational Exposure: Guideline of the Dutch Society of Occupational Hygiene (October 1999)
Bibliographic record
Abstract
Following the recommendations of the European Working Group on Exposure Databases, a Working Group (on Storage of Data of Measurements of Occupational Exposure) of the Dutch Occupational Hygiene Society has developed a Guideline which was presented at the International Symposium on Occupational Exposure Databases and Their Application for the Next Millennium, November 1-3, 1999, London. To establish the present situation, a small-scale telephone survey of monitoring practices and storage of data was done within the Society. The results of the telephone survey and the draft guidance document were discussed with the occupational hygienists and other stakeholders (e.g., authorities, industry, labor unions, and occupational physicians) in a society meeting. This meeting was used to gather ideas on the need and support for a guidance document and to get input for improving the draft guidance document and for implementation of the Guideline. After this meeting, the Guideline was further developed and published by the Dutch Occupational Hygiene Society. The Guideline concentrates on the data elements required when storing exposure data. The data elements presented are the minimum and should be stored minimally to ensure proper interpretation of results at present and in the future and definitions of the items used are given. The Guideline does not prescribe how the data should be stored, or which procedures need to be used to guarantee the quality of the recorded data elements.
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 | 0.038 | 0.061 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.009 |
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".