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Record W2051829145 · doi:10.1136/oem.2009.047720

An improved estimate of the quantitative relationship between polycyclic hydrocarbons and lung cancer

2009· letter· en· W2051829145 on OpenAlexaboutno aff
Dario Mirabelli

Bibliographic record

VenueOccupational and Environmental Medicine · 2009
Typeletter
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsLung cancerPyreneBenzo(a)pyreneCohortEnvironmental scienceEnvironmental healthJob-exposure matrixAluminium smeltingCohort studyDemographyToxicologyMedicineOccupational exposureEnvironmental chemistrySmeltingOncologyChemistryBiologyInternal medicineMetallurgyMaterials scienceSociology

Abstract

fetched live from OpenAlex

In this issue of the journal, Armstrong and Gibbs ( see page 740 ) report the updated results from a mortality study of a large cohort of Quebec aluminium smelter workers.1 2 The focus of their analysis is the quantitative relationship between exposure to polycyclic aromatic hydrocarbons (PAHs) and mortality from lung cancer. Ten more years of follow-up were added along with new cohorts from additional smaller plants for comparison with previously published data3; the study is now the largest ever conducted in aluminium smelting, with 16 431 individuals followed since as far back as 1950 and 677 observed lung cancer deaths.4 More importantly, individual job histories and smoking habits have been recovered, and historical measurements of exposure to benzo[a]pyrene (BaP) and benzene-soluble matter (BSM) could be used to develop a job-exposure matrix (JEM). By applying the JEM, cumulative exposures to BaP and BSM were calculated at the individual level.5 Thus, both statistical power and high quality exposure data were obtained by Armstrong and Gibbs. A new estimate of the slope (and …

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.250
Threshold uncertainty score0.654

Codex and Gemma teacher scores by category

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

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 head0.050
GPT teacher head0.359
Teacher spread0.309 · 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 teacher head, 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

Citations3
Published2009
Admission routes1
Has abstractyes

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