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Record W2127794184 · doi:10.1002/ajim.20036

Ischemic heart disease mortality among heavy equipment operators

2004· article· en· W2127794184 on OpenAlexaffabout
Murray M. Finkelstein, Dave K. Verma, Dru Sahai, Evelyn Stefov

Bibliographic record

VenueAmerican Journal of Industrial Medicine · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsOntario Ministry of LabourMcMaster University
Fundersnot available
KeywordsMedicineOdds ratioInternal medicineEpidemiologyHeart diseaseRetrospective cohort studyCohort studyRespiratory diseaseCardiologySurgeryLung

Abstract

fetched live from OpenAlex

BACKGROUND: Inhalation of fine particulate is hypothesized to increase risk of heart disease events. METHODS: Seven Ontario construction unions participated in a retrospective cohort mortality study. Proportional mortality ratios (PMRs) were computed and a mortality odds ratio (MOR) analysis was performed to compare the risk of ischemic heart disease (IHD) mortality among heavy equipment operators (HEO) to that of members of other unions. Deaths attributed to lung cancer, mesothelioma, and accidental causes were excluded from the comparison. RESULTS: Two hundred fifty nine of 1,009 deaths among the HEO were attributed to IHD. The PMR was 1.09 (0.96-1.2). None of the IHD PMRs among the other six unions exceeded 0.89. The MOR for IHD mortality, comparing the HEO to all other workers combined was 1.47 (1.17-1.84) for ages 25-64, was 1.20 (0.96-1.50) for ages 65 or more, and was 1.32 (1.13-1.55) for all ages combined. CONCLUSIONS: Increased risk of IHD mortality among HEO is consistent with the hypothesis that exposure to diesel fume has adverse effects upon the heart and circulatory system.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.066
GPT teacher head0.339
Teacher spread0.274 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations25
Published2004
Admission routes2
Has abstractyes

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