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Record W2089012355 · doi:10.1179/oeh.2000.6.3.194

Cancer Mortality among Males in Relation to Exposures Assessed through a Job-exposure Matrix

2000· article· en· W2089012355 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Occupational and Environmental Health · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsHealth Canada
Fundersnot available
KeywordsPoisson regressionMedicineDemographyLung cancerJob-exposure matrixRelative riskCancerProstate cancerEnvironmental healthWorkforceOccupational exposureOncologyPopulationConfidence intervalInternal medicine

Abstract

fetched live from OpenAlex

To identify potential associations between workplace exposures and cancer mortality risks, job titles collected from 1965 to 1971 for 58,678 men (a subset of a large representative sample of the Canadian workforce) were transformed into probable chemical exposures using a job-exposure matrix developed in Montreal. Mortality follow-up was determined through computerized record linkage with the National Mortality Database in Canada for 1965-1991. Cancer mortality risk was evaluated at two levels of exposure, any and substantial, using Poisson regression controlling for age, calendar period, and social class. Among the 58,678 men, 3,160 died of cancer. Using a liberal reporting criterion, relative risk (RR) >1.0, five or more exposed cancer deaths, p < or = 0.100, several potential associations were identified, including: lung cancer and any exposure to abrasives dust (RR = 2.84), prostate cancer and any exposure to calcium carbonate (RR = 2.46), and prostate cancer and substantial exposure to metallic dust (RR = 2.13).

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.054
GPT teacher head0.397
Teacher spread0.343 · 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