MétaCan
Menu
Back to cohort
Record W2154339166 · doi:10.1186/bcr3434

COMPLEXO: identifying the missing heritability of breast cancer via next generation collaboration

2013· letter· en· W2154339166 on OpenAlexaff
Melissa C. Southey, Daniel J. Park, Tú Nguyen‐Dumont, Ian Campbell, Ella R. Thompson, Alison H. Trainer, Georgia Chenevix‐Trench, Jacques Simard, Martine Dumont, Penny Soucy, Mads Thomassen, Lars Jønson, Inge Søkilde Pedersen, Thomas van Overeem Hansen, Heli Nevanlinna, Sofia Khan, Olga M. Sinilnikova, Sylvie Mazoyer, Fabienne Lesueur, Francesca Damiola, Rita K. Schmutzler, Alfons Meindl, Eric Hahnen, Michael R. Dufault, TL Chris Chan, Ava Kwong, Rósa B. Barkardóttir, Paolo Radice, Paolo Peterlongo, Peter Devilee, Florentine Hilbers, Javier Benı́tez, Anders Kvist, Therese Törngren, Douglas F. Easton, David J. Hunter, Sara Lindström, Peter Kraft, Wei Zheng, Yu-Tang Gao, Jirong Long, Susan J. Ramus, Bing Feng, Jeffrey N. Weitzel, Katherine L. Nathanson, Kenneth Offit, Joseph Vijai, Mark E. Robson, Kasmintan A. Schrader, San Ming Wang, Yeong C. Kim, Henry T. Lynch, Carrie Snyder, Sean V. Tavtigian, Susan L. Neuhausen, Fergus J. Couch, David E. Goldgar

Bibliographic record

VenueBreast Cancer Research · 2013
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsUniversité Laval
FundersNational Cancer InstituteNational Breast Cancer FoundationSusan G. KomenNational Health and Medical Research CouncilBreast Cancer Research Foundation
KeywordsBreast cancerMissing heritability problemHeritabilityGenetic architectureGenetic associationGeneticsPositional cloningCandidate geneGenetic variationAlleleGenome-wide association studyBiologySurgical oncologyGenetic testingCancerBioinformaticsMedicineOncologyGeneGenotypeGenetic variantsSingle-nucleotide polymorphismQuantitative trait locusPhenotype

Abstract

fetched live from OpenAlex

Linkage analysis, positional cloning, candidate gene mutation scanning and genome-wide association study approaches have all contributed significantly to our understanding of the underlying genetic architecture of breast cancer. Taken together, these approaches have identified genetic variation that explains approximately 30% of the overall familial risk of breast cancer, implying that more, and likely rarer, genetic susceptibility alleles remain to be discovered.

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)0.004
metaresearch head score (Gemma)0.019
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: none
Teacher disagreement score0.016
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0160.018
Insufficient payload (model declined to judge)0.0040.003

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 head0.121
GPT teacher head0.403
Teacher spread0.281 · 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

Citations43
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueBreast Cancer ResearchSame topicBRCA gene mutations in cancerFrench-language works237,207