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Record W2044823121 · doi:10.1038/nbt.1852

Comprehensive assessment of array-based platforms and calling algorithms for detection of copy number variants

2011· article· en· W2044823121 on OpenAlexafffund
Dalila Pinto, Katayoon Darvishi, Xinghua Shi, Diana Rajan, Diane Rigler, Tomas Fitzgerald, Anath C. Lionel, Bhooma Thiruvahindrapuram, Jeffrey R. MacDonald, Ryan E. Mills, Aparna Prasad, Kristin Noonan, Susan Gribble, Elena Prigmore, Patricia K. Donahoe, Richard S. Smith, Ji Hyeon Park, Matthew E. Hurles, Nigel P. Carter, Charles Lee, Stephen W. Scherer, Lars Feuk

Bibliographic record

VenueNature Biotechnology · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomic variations and chromosomal abnormalities
Canadian institutionsUniversity of TorontoSickKids FoundationHospital for Sick Children
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of General Medical SciencesNational Cancer InstituteNational Institutes of HealthNational Human Genome Research InstituteNederlandse Organisatie voor Wetenschappelijk OnderzoekWellcome TrustHospital for Sick ChildrenScheme for Promotion of Academic and Research CollaborationGöran Gustafssons StiftelserCanadian Institutes of Health ResearchGenome Canada
KeywordsReplicateCopy-number variationConcordanceBenchmark (surveying)Computer scienceRaw dataReproducibilityData miningComputational biologyBioinformaticsBiologyStatisticsGeneticsMathematicsGenomeGeneCartography

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)0.014
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.022
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.017
GPT teacher head0.272
Teacher spread0.255 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations422
Published2011
Admission routes2
Has abstractno

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