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Record W1973550734 · doi:10.1007/s10549-005-1409-1

Breast cancer predisposing alleles in Poland

2005· article· en· W1973550734 on OpenAlexaff
Bohdan Górski, Cezary Cybulski, Tomasz Huzarski, Tomasz Byrski, Jacek Gronwald, Anna Jakubowska, Małgorzata Stawicka, S. Gozdecka-Grodecka, Marek Szwiec, Krzysztof Urbański, Jerzy Mituś, Elżbieta Marczyk, Ireneusz Dziuba, Piotr Wandzel, Dariusz Surdyka, Olga Haus, H Janiszewska, Tadeusz Dębniak, A. Tołoczko-Grabarek, Krzysztof Mędrek, Bartłomiej Masojć, Marek Mierzejewski, E Kowalska, Steven A. Narod, Jan Lubiński

Bibliographic record

VenueBreast Cancer Research and Treatment · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsCoalition for Research in Women's HealthUniversity of Toronto
Fundersnot available
KeywordsBreast cancerCHEK2Missense mutationAlleleGeneticsPopulationOdds ratioBiologyMutationCancerOncologyInternal medicineMedicineGeneGermline mutation

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.030
GPT teacher head0.363
Teacher spread0.333 · 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

Citations126
Published2005
Admission routes1
Has abstractno

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