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Record W2989673129 · doi:10.1186/s12920-019-0618-0

Return of genetic and genomic research findings: experience of a pediatric biorepository

2019· article· en· W2989673129 on OpenAlexafffund
Tanya Papaz, Eriskay Liston, Laura Zahavich, Dimitri J. Stavropoulos, Rebekah Jobling, Raymond H. Kim, Miriam S. Reuter, Anastasia Miron, Erwin Oechslin, Tapas Mondal, Lynn Bergin, John Smythe, Luis Altamirano‐Diaz, Jane Lougheed, Roderick Yao, Oyediran Akinrinade, Jeroen Breckpot, Seema Mital

Bibliographic record

VenueBMC Medical Genomics · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsKingston General HospitalLondon Health Sciences CentreMcMaster Children's HospitalUniversity of TorontoSickKids FoundationUniversity Health NetworkChildren's Hospital of Eastern OntarioTed Rogers Centre for Heart ResearchHospital for Sick Children
FundersHospital for Sick ChildrenHeart and Stroke Foundation of Canada
KeywordsBiorepositoryGenetic counselingBiobankMedicineReferralGenetic testingFamily medicineHuman geneticsMedical geneticsBioinformaticsInternal medicineGenetics

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.039
metaresearch head score (Gemma)0.060
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 score0.039
Threshold uncertainty score0.205

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.060
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0030.003
Open science0.0030.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.019
GPT teacher head0.292
Teacher spread0.273 · 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
Published2019
Admission routes2
Has abstractyes

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