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Record W2168897729 · doi:10.1186/1745-6673-3-18

Finding toxicological information: An approach for occupational health professionals

2008· article· en· W2168897729 on OpenAlexaboutno aff
Irja Laamanen, Jos Verbeek, Giuliano Franco, Marika M Lehtola, Marita Luotamo

Bibliographic record

VenueJournal of Occupational Medicine and Toxicology · 2008
Typearticle
Languageen
FieldChemistry
TopicHistory and advancements in chemistry
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHealth professionalsPublic healthOccupational exposureEnvironmental healthNursingHealth care

Abstract

fetched live from OpenAlex

BACKGROUND: It can be difficult for occupational health professionals to assess which toxicological databases available on the Internet are the most useful for answering their questions. Therefore we evaluated toxicological databases for their ability to answer practical questions about exposure and prevention. We also propose recommended practices for searching for toxicological properties of chemicals. METHODS: We used a systematic search to find databases available on the Internet. Our criteria for the databases were the following: has a search engine, includes factual information on toxic and hazardous chemicals harmful for human health, and is free of charge. We developed both a qualitative and a quantitative rating method, which was used by four independent assessors to determine appropriateness, the quality of content, and ease of use of the database. Final ratings were based on a consensus of at least two evaluators. RESULTS: Out of 822 results we found 21 databases that met our inclusion criteria. Out of these 21 databases 14 are administered in the US, five in Europe, one in Australia, and one in Canada. Nine are administered by a governmental organization. No database achieved the maximum score of 27. The databases GESTIS, ESIS, Hazardous Substances Data Bank, TOXNET and NIOSH Pocket Guide to Chemical Hazards all scored more than 20 points. The following approach was developed for occupational health professionals searching for the toxicological properties of chemicals: start with the identity of the chemical; then search for health hazards, exposure route and measurement; next the limit values; and finally look for the preventive measures. CONCLUSION: A rating system of toxicological databases to assess their value for occupational health professionals discriminated well between databases in terms of their appropriateness, quality of information, and ease of use. Several American and European databases yielded high scores and provide a valuable source for occupational health professionals.

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 imitation

Not 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.

metaresearch head score (Codex)0.183
metaresearch head score (Gemma)0.204
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.986
Threshold uncertainty score0.970

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1830.204
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0320.016
Science and technology studies0.0080.009
Scholarly communication0.0140.017
Open science0.0080.018
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0040.002

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.

Opus teacher head0.161
GPT teacher head0.422
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations5
Published2008
Admission routes1
Has abstractyes

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