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Record W2023055872 · doi:10.2217/ahe.13.21

Mammography Screening for Women Aged 75 Years or More

2013· article· en· W2023055872 on OpenAlexaff
Anthony B. Miller

Bibliographic record

VenueAging Health · 2013
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsPublic Health Ontario
Fundersnot available
KeywordsMedicineMammographyBreast cancerLife expectancyRandomized controlled trialIncidence (geometry)Breast cancer screeningMammography screeningGynecologyScreening mammographyClinical trialCancerInternal medicinePopulationEnvironmental health

Abstract

fetched live from OpenAlex

Evaluation of: Schonberg MA, Breslau ES, McCarthy EP. Targeting of mammography screening according to life expectancy in women aged 75 and older. J. Am. Geriatr. Soc. 61(3), 388–395 (2013). The evidence on the effectiveness of mammography screening for women aged 75 years or more has been reviewed. As there is no randomized screening trial evidence of benefit, the evidence from trials involving younger women have to be extrapolated. However, the relevant trials were performed before recent advances in breast cancer treatment were available, thus the absolute degree of benefit has to be much less than estimated from the trials. Recent trends in breast cancer incidence and mortality in the USA are considered. The majority of deaths from breast cancer in women aged 75 years or more are from cases diagnosed at younger ages. It is probable that less than one in 6000 women aged 75 years or more would benefit from mammography screening.

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)0.001
metaresearch head score (Gemma)0.003
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: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0090.001

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 head0.098
GPT teacher head0.389
Teacher spread0.291 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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