Record W4249058187 · doi:10.1109/isbi.2015.7163794

Organizing Committee

2015· article· en· W4249058187 on OpenAlexfundno aff

Bibliographic record

Venuenot available

Typearticle

Languageen

FieldComputer Science

TopicEducational Robotics and Engineering

Canadian institutionsnot available

FundersLawrence Berkeley National LaboratoryRobarts Research InstituteWake Forest School of MedicineUniversity of California, DavisWeill Cornell Medical CollegeHaute école Spécialisée de Suisse OccidentaleDebreceni EgyetemAkademia Górniczo-Hutnicza im. Stanislawa StaszicaUniversité de Rennes 1Université de BordeauxUniversità degli Studi di VeronaUniversidad de la República UruguayNational and Kapodistrian University of AthensLeids Universitair Medisch CentrumAarhus UniversitetSiemensK.N.Toosi University of TechnologyNational Institutes of HealthTehran University of Medical Sciences and Health ServicesMauna Kea TechnologiesUniversità degli Studi di FirenzeUniversity of California, San DiegoJohns Hopkins UniversityUniversität zu LübeckRadboud UniversiteitPusan National UniversityGentofte HospitalChinese Academy of SciencesUniversitat Pompeu FabraInstitut National de la Santé et de la Recherche MédicaleUniversität HeidelbergNanyang Technological UniversityUniversità degli Studi di PadovaSimon Fraser UniversityUniversity of MissouriDeutsches KrebsforschungszentrumNorthwestern Polytechnical UniversityCentre National de la Recherche ScientifiqueKing's College LondonUniversity of LouisvilleImperial College LondonUniversity of Southern CaliforniaUniversity of MemphisRutgers, The State University of New JerseyUniversity of Texas at ArlingtonPennsylvania State UniversityIndian National Science AcademyInstitut national de recherche en informatique et en automatique (INRIA)McGill UniversityLehigh UniversityUniversidad de ValladolidHenry Ford Health SystemFlorida International UniversityNorthwestern UniversityCalifornia Institute of TechnologyUniversity of PennsylvaniaUniversity College LondonCommonwealth Scientific and Industrial Research OrganisationAarhus UniversitetshospitalWayne State UniversityYale UniversityUniversity of Cape TownChinese University of Hong KongMassachusetts General HospitalVillanova UniversityBrigham and Women's Hospital

KeywordsComputer science

DOI10.1109/isbi.2015.7163794

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)0.011

metaresearch head score (Gemma)0.013

Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated

Candidate categoriesInsufficient payload (model declined to judge)

Consensus categoriesInsufficient payload (model declined to judge)

DomainCandidate signal: none · Consensus signal: none

Study designCandidate signal: Not applicable · Consensus signal: Not applicable

GenreCandidate signal: Other · Consensus signal: Other

Teacher disagreement score0.662

Threshold uncertainty score0.945

Distilled classifier scores by category (both heads)

Category	Codex	Gemma
Metaresearch	0.011	0.013
Meta-epidemiology (narrow)	0.001	0.001
Meta-epidemiology (broad)	0.001	0.001
Bibliometrics	0.004	0.002
Science and technology studies	0.004	0.001
Scholarly communication	0.011	0.003
Open science	0.003	0.005
Research integrity	0.006	0.004
Insufficient payload (model declined to judge)	0.338	0.347

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 head0.044

GPT teacher head0.241

Teacher spread0.196 · 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