MétaCan
Menu
Back to cohort
Record W2017319820 · doi:10.1007/s10549-010-1036-3

International distribution and age estimation of the Portuguese BRCA2 c.156_157insAlu founder mutation

2010· article· en· W2017319820 on OpenAlexafffund
Ana Peixoto, Catarina Santos, Manuela Pinheiro, Pedro Pinto, Maria José Soares, Patrícia Rocha, Leonor Gusmão, António Amorim, Annemarie van der Hout, Anne‐Marie Gerdes, Mads Thomassen, Torben A. Kruse, Dorthe Gylling Crüger, Lone Sunde, Yves–Jean Bignon, Nancy Uhrhammer, L Cornil, Étienne Rouleau, Rosette Lidereau, Drakoulis Yannoukakos, Maroulio Pertesi, Steven A. Narod, Robert E. Royer, Maurício Magalhães Costa, Conxi Lázaro, Lídia Feliubadaló, Begoña Graña, Ignacio Blanco, Miguel de la Hoya, Philippe Maillet, Gaëlle Benais-Pont, Bruno Pardo, Yael Laitman, Eitan Friedman, Eladio A. Velasco, M. Durán, María-Dolores Miramar, Ana Rodríguez Valle, María-Teresa Calvo, Ana Vega, Ana Blanco, Orland Dı́ez, Sara Gutiérrez‐Enríquez, Judith Balmañà, Teresa Ramón y Cajal, Carmen Alonso, Montserrat Baiget, William D. Foulkes, Marc Tischkowitz, Rachel Kyle, Nelly Sabbaghian, Patrícia Ashton‐Prolla, Ingrid Petroni Ewald, Thangarajan Rajkumar, Luísa Mota‐Vieira, Giuseppe Giannini, Alberto Gulino, Maria Isabel Achatz, Dirce Maria Carraro, Brigitte Bressac–de Paillerets, Audrey Remenieras, Cindy Benson, Silvia Casadei, Mary‐Claire King, Erik Teugels, Manuel R. Teixeira

Bibliographic record

VenueBreast Cancer Research and Treatment · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsMcGill UniversityMcGill University Health CentreJewish General HospitalWomen's College HospitalUniversity of Toronto
FundersMinistério da SaúdeMinisterio de Ciencia e InnovaciónJewish General HospitalLiga Portuguesa Contra o CancroHospital de Clínicas de Porto AlegreConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorSusan G. Komen for the Cure
KeywordsFounder effectBreast cancerPortugueseEstimationMutationGeneticsMedicineBiologyOncologyDemographyCancerGeneGenotypeHaplotypeSociology

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
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
Bibliometrics0.0040.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.026
GPT teacher head0.356
Teacher spread0.330 · 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

Citations36
Published2010
Admission routes2
Has abstractno

Explore more

Same venueBreast Cancer Research and TreatmentSame topicBRCA gene mutations in cancerFrench-language works237,207