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Record W4253002007 · doi:10.3747//co.19.1003

A model for breast cancer risk based on stem-cell theory

2012· article· en· W4253002007 on OpenAlexaffvenueabout
S. A. Narod

Bibliographic record

VenueCurrent Oncology · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsWomen's College Hospital
Fundersnot available
KeywordsCitationMedicineBreast cancerFamily medicineGerontologyLibrary scienceCancerInternal medicineComputer science

Abstract

fetched live from OpenAlex

Open AccessEditorial A Model for Breast Cancer Risk Based on Stem-Cell Theory by S.A. Narod Women's College Research Institute, Women's College Hospital and the Dalla Lana School of Public Health, University of Toronto, 790 Bay Street, 7th floor, Toronto, ON M5G 1N8, Canada Curr. Oncol. 2012, 19(1), 9-11; https://doi.org/10.3747/co.19.1003 Received: 10 November 2011 / Revised: 9 December 2011 / Accepted: 13 January 2012 / Published: 1 February 2012 Download PDF Citation Export BibTeX EndNote RIS Cite This Paper

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)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0030.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0180.002

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 head0.047
GPT teacher head0.346
Teacher spread0.299 · 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 designTheoretical or conceptual
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
Published2012
Admission routes3
Has abstractyes

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