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Record W4283331147 · doi:10.1097/jom.0000000000002606

Breast Cancer Among Female Flight Attendants and the Role of the Occupational Exposures

2022· review· en· W4283331147 on OpenAlexaboutno aff
Sandra Weinmann, Luana Fiengo Tanaka, Günther Schauberger, Vanesa Osmani, Stefanie J. Klug

Bibliographic record

VenueJournal of Occupational and Environmental Medicine · 2022
Typereview
Languageen
FieldMedicine
TopicRadiation Therapy and Dosimetry
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCircadian rhythmIncidence (geometry)Confidence intervalBreast cancerObservational studyMeta-analysisDemographyEnvironmental healthInternal medicineCancer

Abstract

fetched live from OpenAlex

OBJECTIVE: We conducted a systematic review and meta-analysis to investigate occupational exposures and their role in breast cancer (BC) risk among female flight attendants (FFAs). METHODS: We systematically searched PubMed and EMBASE and included all observational studies reporting on the outcome BC incidence among FFAs. The exposures of interest were cosmic radiation and circadian rhythm disruption. Study quality was assessed using the Newcastle-Ottawa Scale. RESULTS: Nine studies met the inclusion criteria, of which four were included in the meta-analysis for BC incidence (pooled standardized incidence ratio, 1.43; 95% confidence interval, 1.32 to 1.54). Three studies suggested a possible association between BC and cosmic radiation, whereas none found an association with circadian rhythm disruption. CONCLUSION: Neither exposure to cosmic radiation nor circadian rhythm disruption seems to explain the elevated risk of BC among flight attendants. Further studies reporting individual information on occupational exposures are needed.

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)0.008
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.023
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.017
Bibliometrics0.0070.006
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.312
Teacher spread0.285 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations11
Published2022
Admission routes1
Has abstractyes

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