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Record W3165849909 · doi:10.1002/ajim.23257

Malignant mesothelioma: Ongoing controversies about its etiology in females

2021· article· en· W3165849909 on OpenAlexaff
Xaver Baur, Arthur L. Frank, Colin L. Soskolne, L. Christine Oliver, Corrado Magnani

Bibliographic record

VenueAmerican Journal of Industrial Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicOccupational and environmental lung diseases
Canadian institutionsPublic Health OntarioUniversity of TorontoUniversity of Alberta
Fundersnot available
KeywordsMedicineMesotheliomaEtiologyAsbestosPathologyIntensive care medicineInternal medicineOncology

Abstract

fetched live from OpenAlex

Malignant mesothelioma (MM) is one of the most aggressive cancers with the poorest of outcomes. There is no doubt that mesothelioma in males is related to asbestos exposure, but some authors suggest that most of the cases diagnosed in females are "idiopathic." In our assessment of the science, the "low risk" of mesothelioma in females is because of the nonsystematic recording of exposure histories among females. Indeed, asbestos exposure is mentioned in only some of the studies that include females. We estimate the risk of MM among females to be close to that in males. The absence of detailed exposure histories should be rectified in future studies involving ​women. As a matter of social justice, the ongoing failure to recognize asbestos as the cause of a majority of cases of MM in females does them, and their kin, a profound disservice.

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)0.013
metaresearch head score (Gemma)0.026
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.007
Scholarly communication0.0030.007
Open science0.0020.002
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0030.001

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 head0.045
GPT teacher head0.306
Teacher spread0.261 · 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

Citations12
Published2021
Admission routes1
Has abstractyes

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