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Record W4408272685 · doi:10.4218/etr2.70008

2024 Reviewer List

2025· article· en· W4408272685 on OpenAlexfundno aff

Bibliographic record

VenueETRI Journal · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
FundersOak Ridge National LaboratoryNational Institute of Information and Communications TechnologyQingdao UniversityElectronics and Telecommunications Research InstituteQueen's UniversityKorea UniversityKorea Maritime and Ocean UniversityPohang University of Science and TechnologyTencentKunsan National UniversityQueen's University BelfastAsia UniversityMenofia UniversityAjou UniversityUniversity of SydneyChungbuk National UniversityHanyang UniversityJamia Millia IslamiaIndian Institute of Information Technology, AllahabadSoutheast UniversityKorea Advanced Institute of Science and TechnologyUniversity of WashingtonDalian Maritime UniversityIran Telecommunication Research CenterNational Institute of Technology WarangalCity University of Hong Kong
KeywordsComputer sciencePsychologyMedicine

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)0.364
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: none
Teacher disagreement score0.674
Threshold uncertainty score0.961

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.364
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0140.006
Science and technology studies0.0050.002
Scholarly communication0.0120.005
Open science0.0030.005
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.3260.176

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 head0.041
GPT teacher head0.239
Teacher spread0.198 · 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 abstractno

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