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Record W2016413295 · doi:10.1102/1470-7330.2005.0022

Should we use MRI to screen women at high-risk of breast cancer?

2005· article· en· W2016413295 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCancer Imaging · 2005
Typearticle
Languageen
FieldMedicine
TopicBreast Lesions and Carcinomas
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBreast cancerMammographyAsymptomaticMagnetic resonance imagingBreast densityBreast MRIFamily historyLifetime riskBreast cancer screeningDiseaseCancerRadiologyOncologyGynecologyInternal medicine

Abstract

fetched live from OpenAlex

Women with a strong family history of breast cancer are at increased risk of developing the disease themselves. Mammographic surveillance is recommended in the over 40 age group but the evidence of benefit from this strategy is limited until the individual reaches age 50 years. There is increasing evidence from the trials of breast magnetic resonance imaging that women at high risk may benefit from this technique as sensitivity is not dependent on breast density. The Dutch and Canadian studies have reported the sensitivity of MRI to be 71% and 77% compared to mammography which was 40% and 36%, respectively, in asymptomatic high risk cohorts.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score1.000

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)0.0020.000

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 head0.024
GPT teacher head0.290
Teacher spread0.266 · 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