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Record W1995683190 · doi:10.1038/nmeth.1931

Protein interaction data curation: the International Molecular Exchange (IMEx) consortium

2012· article· en· W1995683190 on OpenAlexafffund
Sandra Orchard, Samuel Kerrien, Sara Abbani, Bruno Aranda, Jignesh Bhate, Shelby Bidwell, Alan Bridge, Leonardo Briganti, Fiona S. L. Brinkman, Gianni Cesareni, Andrew Chatr‐aryamontri, Émilie Chautard, Carol Chen, Marine Dumousseau, Johannes B. Goll, Robert E. W. Hancock, Linda I. Hannick, Igor Jurišica, Jyoti Khadake, David J. Lynn, Usha Mahadevan, Livia Perfetto, Arathi Raghunath, Sylvie Ricard‐Blum, Bernd Roechert, Łukasz Salwiński, Volker Stümpflen, Mike Tyers, Peter Uetz, Ioannis Xénarios, Henning Hermjakob

Bibliographic record

VenueNature Methods · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioinformatics and Genomic Networks
Canadian institutionsUniversity Health NetworkUniversity of British ColumbiaOntario Institute for Cancer ResearchMount Sinai HospitalLunenfeld-Tanenbaum Research InstituteSimon Fraser University
FundersFP7 HealthNational Institutes of HealthCanadian Institutes of Health ResearchEuropean CommissionNational Institute of General Medical SciencesWellcome Trust
KeywordsData curationInterface (matter)Set (abstract data type)Computer scienceData exchangeQuality (philosophy)Data scienceComputational biologyWorld Wide WebBiology

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)0.020
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.026
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0120.011
Science and technology studies0.0030.001
Scholarly communication0.0060.005
Open science0.0080.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0320.032

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 head0.033
GPT teacher head0.381
Teacher spread0.347 · 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 designNot applicable
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

Citations576
Published2012
Admission routes2
Has abstractno

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