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Record W2737732224 · doi:10.1038/gim.2017.80

Data sharing as a national quality improvement program: reporting on BRCA1 and BRCA2 variant-interpretation comparisons through the Canadian Open Genetics Repository (COGR)

2017· article· en· W2737732224 on OpenAlexafffundabout
Matthew S. Lebo, Kathleen-Rose Zakoor, Kathy Chun, Marsha Speevak, John S. Waye, M. Elizabeth McCready, Jillian S. Parboosingh, Ryan E. Lamont, Harriet Feilotter, Ian Bosdet, Tracy Tucker, Sean Young, Aly Karsan, George S. Charames, Ronald Agatep, Elizabeth Spriggs, Caitlin Chisholm, Nasim Vasli, Hussein Daoud, Olga Jarinova, Robert Tomaszewski, Stacey Hume, Sherryl A. Taylor, Mohammad R. Akbari, Jordan Lerner‐Ellis, Ron Agatep, Peter Ainsworth, Melyssa Aronson, Raveen Basran, André Blavier, Andrea Blumenthal, Kym M. Boycott, Michael Brudno, Kathleen Buckley, Jodi Campbell, Philippe M. Campeau, Melanie Care, Nancy Carson, Ronald Carter, David Chitayat, George Chong, E. Chouinard, Kenneth J. Craddock, Roderick Docking, Andrea Eisen, Hanna Faghfoury, Sandra A. Farrell, Bridget A. Fernandez, Marc Fiume, Cynthia Forster‐Gibson, Jan M. Friedman, William D. Foulkes, Peter Goodhand, Jessica Gu, Robert A. Hegele, Spring Holter, Sheri Horsburgh, Lauren Hughes, Franny Jewett, Anne Junker, Sam Khalouei, Joan H.M. Knoll, Elena Kolomeitz, Bartha Maria Knoppers, Georges Maire, Christian R. Marshall, Grant Mitchell, Michael Moorhouse, Chantal F. Morel, Tanya N. Nelson, Abdul Noor, Brian D. O’Connor, Darren D. O’Rielly, B. F. Francis Ouellette, Hilary Racher, Peter C. Ray, Heidi L. Rehm, Christie Riddell, Jean‐Baptiste Rivière, David S. Rosenblatt, Guy A. Rouleau, Andrea Ruchon, Peter Sabatini, Bekim Sadiković, Kara Semotiuk, Stephen W. Scherer, Cheryl Shuman, Josh Silver, Katherine A. Siminovitch, Lesley Solomon-Izsak, Jean‐François Soucy, James Stavropoulos, Lincoln Stein, Rhonda Tannenbaum, Deborah Terespolsky, Richard F. Wintle, Beatrix Wong, Nora Wong, Marina Wang, Nicholas A. Watkins, Shana White, Michael O. Woods, Philip Wyatt

Bibliographic record

VenueGenetics in Medicine · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsOntario Institute for Cancer ResearchUniversity of AlbertaChildren's Hospital of Eastern OntarioShared HealthSinai Health SystemBC Cancer AgencyQueen's UniversityAlberta Children's HospitalLunenfeld-Tanenbaum Research InstituteMount Sinai HospitalUniversity of CalgaryUniversity of TorontoHamilton Health SciencesWomen's College HospitalCredit Valley HospitalUniversity of ManitobaTrillium Health CentreHamilton Regional Laboratory Medicine ProgramNorth York General Hospital
FundersCanadian Institutes of Health ResearchGovernment of CanadaOntario GenomicsOntario Genomics InstituteGenome Canada
KeywordsTier 2 networkTier 1 networkUploadMedicineQuality (philosophy)MEDLINEComputer scienceBiologyWorld Wide Web

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)0.260
metaresearch head score (Gemma)0.507
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Open science
Consensus categoriesMetaresearch
DomainCandidate signal: Reproducibility · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score0.912

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2600.507
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0200.037
Science and technology studies0.0070.003
Scholarly communication0.0090.005
Open science0.0130.012
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0190.005

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 head0.153
GPT teacher head0.443
Teacher spread0.291 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designObservational
DomainReproducibility
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

Citations31
Published2017
Admission routes3
Has abstractno

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