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Record W2074568559 · doi:10.1097/jom.0b013e318216d0b3

Breast Cancer Risk Associated With Residential Proximity to Industrial Plants in Canada

2011· article· en· W2074568559 on OpenAlexaffabout
Sai Yi Pan, Howard Morrison, Laurie Gibbons, Jia Zhou, Shi Wu Wen, Marie DesMeules, Yang Mao

Bibliographic record

VenueJournal of Occupational and Environmental Medicine · 2011
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsPublic Health Agency of Canada
Fundersnot available
KeywordsOil refineryBreast cancerEnvironmental scienceWaste managementSmeltingEnvironmental healthMedicineEngineeringCancerMetallurgyMaterials science

Abstract

fetched live from OpenAlex

OBJECTIVE: The relationship between breast cancer risk and residential proximity to paper mills, pulp mills, petroleum refineries, steel mills, thermal power plants, alum smelters, nickel smelters, lead smelters, copper smelters, and zinc smelters was assessed. METHODS: We conducted a population-based case-control study of 2343 cases with breast cancer and 2467 controls using residential proximity at some time between 1960 and 5 years before the completion of questionnaire in Canada. RESULTS: Adjusted odds ratios were statistically significantly increased for residing near steel mills (0.8 to 3.2 km) and thermal power plants (<0.8 km) in premenopausal women, petroleum refinery (0.8 to 3.2 km) and pulp mills (0.8 to 3.2 km) in postmenopausal women, and for 10 or more years of residing near thermal power plants of 0.8 km. CONCLUSIONS: Our preliminary results suggested possible weak associations between breast cancer and proximity to steel mills, pulp mills, petroleum refineries, and thermal power plants.

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 score0.064
Threshold uncertainty score0.633

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.082
GPT teacher head0.286
Teacher spread0.204 · 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

Citations31
Published2011
Admission routes2
Has abstractyes

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