MétaCan
Menu
Back to cohort
Record W7097357825

BREAST CANCER IN CIRCUMPOLAR INUIT 1969- 1988

2016· article· en· W7097357825 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsnot available
Fundersnot available
KeywordsBreast cancerCircumpolar starIncidence (geometry)ObesityCancerPublic healthFamily history
DOInot available

Abstract

fetched live from OpenAlex

Breast cancer was studied over a 20-year period in Inuit populations in the Circumpolar region. A total of 193 breast cancers were observed in women. The incidence increased from 28.2 per 100 000 in 1969-1973 to 34.3 per 100 000 in 1984-1988. However, the incidence is low, about half what could be expected based on the rates in Denmark, Canada and Connecticut (USA). The low incidence could be explained by the Inuit diet and other lifestyle factors. These benefits should be preserved, in particular in the young, to maintain a low breast cancer incidence. Breast cancer in women attracts worldwide attention being the most frequent cancer site among women in western societies (1). Breast cancer rates have been increas-ing in most countries ( I, 2) and though a number of risk factors for breast cancer are known, such as high fat diet, older age at first pregnancy, nulliparity, a family history of breast cancer, high level of estrogens, obesity in post-menopausal women, etc., it has so far only been possible to offer general advice to the public on how to prevent the

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)0.000
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 score0.788
Threshold uncertainty score0.421

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.013
GPT teacher head0.286
Teacher spread0.273 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

Explore more

Same topicCancer Risks and FactorsFrench-language works237,207