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Record W4226251227 · doi:10.1038/s41592-021-01327-9

Towards community-driven metadata standards for light microscopy: tiered specifications extending the OME model

2021· article· en· W4226251227 on OpenAlexaff
Mathias Hammer, Maximiliaan Huisman, Alessandro Rigano, Ulrike Boehm, James J. Chambers, Nathalie Gaudreault, Alison J. North, Jaime A. Pimentel, Damir Sudar, Peter Bajcsy, Claire M. Brown, Alexander D. Corbett, Orestis Faklaris, Judith Lacoste, Alex Laude, Glyn Nelson, Farzin Farzam, Carlas Smith, David Grünwald, Caterina Strambio‐De‐Castillia

Bibliographic record

VenueNature Methods · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsMcGill University
FundersNational Institute of Biomedical Imaging and BioengineeringFogarty International CenterNational Cancer InstituteRIKENNational Institute of Standards and TechnologyNational Institute on Drug AbuseNederlandse Organisatie voor Wetenschappelijk OnderzoekAgence Nationale de la RechercheDeutsche ForschungsgemeinschaftInfrastructures en Biologie Santé et AgronomieChan Zuckerberg InitiativeSilicon Valley Community FoundationNational Institutes of HealthNational Science Foundation
KeywordsMetadataComputer scienceMicroscopyScale (ratio)Data qualityQuality (philosophy)Data scienceData miningWorld Wide WebCartographyEngineeringMedicinePathologyPhysics

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)0.068
metaresearch head score (Gemma)0.082
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.982
Threshold uncertainty score0.360

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0680.082
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0080.006
Science and technology studies0.0040.006
Scholarly communication0.0180.026
Open science0.0100.022
Research integrity0.0080.011
Insufficient payload (model declined to judge)0.0050.005

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 head0.051
GPT teacher head0.440
Teacher spread0.389 · 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.

Study designTheoretical or conceptual
DomainReporting
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

Citations58
Published2021
Admission routes1
Has abstractno

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