MétaCan
Menu
Back to cohort
Record W1764005853 · doi:10.1038/ng.3304

Factors influencing success of clinical genome sequencing across a broad spectrum of disorders

2015· article· en· W1764005853 on OpenAlexaff
Jenny C. Taylor, Hilary C. Martin, Stefano Lise, John Broxholme, Jean‐Baptiste Cazier, Andy Rimmer, Alexander Kanapin, Gerton Lunter, Simon Fiddy, Chris Allan, A.R. Aricescu, Moustafa Attar, Christian Babbs, Jennifer Becq, David Beeson, Celeste Bento, P Bignell, Edward Blair, Veronica J. Buckle, Katherine R. Bull, Ondřej Cais, Holger Cario, Helen Chapel, Richard R. Copley, Richard J. Cornall, Jude Craft, Karin Dahan, Emma E. Davenport, Calliope A. Dendrou, Olivier Devuyst, Aimée L Fenwick, Jonathan Flint, Lars Fugger, Rodney D. Gilbert, Anne Goriely, Angie Green, Ingo H. Greger, Russell Grocock, Anja V. Gruszczyk, Robert Hastings, Edouard Hatton, Douglas R. Higgs, Adrian V. S. Hill, Chris Holmes, Malcolm F. Howard, Linda Hughes, Peter Humburg, David H. Johnson, Fredrik Karpe, Zoya Kingsbury, Usha Kini, Julian C. Knight, Jonathan Krohn, Sarah Lamble, Craig B. Langman, Lorne Lonie, Joshua Luck, Davis J. McCarthy, Simon J. McGowan, Mary Frances McMullin, Kerry A. Miller, Lisa Murray, Andrea H. Németh, M. Andrew Nesbit, David Nutt, Elizabeth Ormondroyd, Annette Oturai, Alistair T. Pagnamenta, Smita Y. Patel, Melanie J. Percy, Nayia Petousi, Paolo Piazza, Siân E. Piret, Guadalupe Polanco‐Echeverry, Niko Popitsch, Fiona Powrie, Christopher W. Pugh, Lynn Quek, Peter A. Robbins, Kathryn Robson, Alexandra Russo, Natasha Sahgal, Pauline A. van Schouwenburg, Anna Schuh, Earl D. Silverman, Alison Simmons, Per Soelberg Sørensen, Elizabeth Sweeney, John Taylor, Rajesh V. Thakker, Ian Tomlinson, Amy Trebes, Stephen R.F. Twigg, Holm H. Uhlig, Paresh Vyas, Tim J. Vyse, Steven A. Wall, Hugh Watkins, Michael P. Whyte, Lorna Witty, Christopher Yau, David Buck, Sean Humphray, Peter J. Ratcliffe, John I. Bell, Andrew O.M. Wilkie, David Bentley, Peter Donnelly, Gil McVean

Bibliographic record

VenueNature Genetics · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics and Rare Diseases
Canadian institutionsHospital for Sick Children
FundersBiotechnology and Biological Sciences Research CouncilMedical Research CouncilSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Institute for Health and Care ResearchCancer Research UKAction Medical ResearchAcademy of Medical SciencesBritish Heart FoundationWellcome Trust
KeywordsBiologyBroad spectrumGeneticsComputational biologyGenomeDNA sequencingEvolutionary biologyGene

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)0.033
metaresearch head score (Gemma)0.186
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 score0.033
Threshold uncertainty score0.176

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.186
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0010.002
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 head0.028
GPT teacher head0.340
Teacher spread0.312 · 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

Citations388
Published2015
Admission routes1
Has abstractno

Explore more

Same venueNature GeneticsSame topicGenomics and Rare DiseasesFrench-language works237,207