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Record W7128545246 · doi:10.1111/emre.12660

Issue Information

2025· article· en· W7128545246 on OpenAlexfundno aff

Bibliographic record

VenueEuropean Management Review · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
FundersBusiness School, University of AucklandAarhus Institute of Advanced Studies, Aarhus UniversitetHEC MontréalUniversiteit van TilburgSyddansk UniversitetTel Aviv UniversityI-Shou UniversityLunds UniversitetRadboud UniversiteitUniversité de PoitiersRijksuniversiteit GroningenUniversity of LimerickUniversité de Recherche Paris Sciences et LettresUniversity of ReadingUniversità di BolognaCopenhagen Business SchoolUniversity of SussexUniversité du Québec à MontréalUniversity College LondonUniversity of SouthamptonUniversity of LeedsUniversitat Pompeu FabraKorea Advanced Institute of Science and TechnologyCoventry UniversityDartmouth CollegeUniversità degli Studi di CagliariUniversity of WolverhamptonUniversità degli Studi di Enna KoreUniversité de LilleSveriges LantbruksuniversitetPontifícia Universidade Católica de Minas GeraisTeesside UniversityLappeenranta University of TechnologyMiddlesex UniversityLudwig-Maximilians-Universität MünchenLahore University of Management SciencesUniversität BaselUniversidad de NavarraUtah State UniversityGeorgia State UniversityBentley UniversityUniversità degli Studi della Campania Luigi VanvitelliUniversity of Virginia
KeywordsInformation systemInformation technologyField (mathematics)

Abstract

fetched live from OpenAlex

No abstract is available for this article.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.002
metaresearch head score (Gemma)0.011
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 score0.074
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0010.000
Scholarly communication0.0050.003
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.9260.828

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 head0.022
GPT teacher head0.211
Teacher spread0.190 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2025
Admission routes1
Has abstractyes

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