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Record W4247225041 · doi:10.1109/crv50864.2020.00007

CRV 2020 Committees

2020· article· en· W4247225041 on OpenAlexaff
Abdelrahman Abdelhamed, Abhijith Punnappurath, Alexander Andreopoulos, Alexander Ferworn, Ali Harakeh, Alvaro Uribe Quevedo, Boris N. Oreshkin, Element Ai, Bryan Tripp, Carlos Vázquez, Cunjian Chen, Daniel Asmar, Daniel Buckstein, David A. Clausi, David Meger, Dhanesh Ramachandram, Éric Granger, Ets Montreal, Fahim Mannan, Algolux Faisal Qureshi, François Pomerleau, Graham W. Taylor, Guillaume-Alexandre Bilodeau, Gunho Sohn, Hughes Perreault, Hui-Lee Ooi, J. Krishna Murthy, Jack Collier, Drdc Suffield, James J. Clark, James H. Elder, Jean‐François Lalonde, Jianhui Chen, Jimmy Li, Jochen Lang, John Zelek, Kaleem Siddiqi, Konstantinos G. Derpanis, Krista A. Ehinger, Mahmoud Afifi, Mark Eramian, Mathieu Garon, Maxime Tremblay, Michael Fulton, Michael Greenspan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Perspectives in Modern Studies
Canadian institutionsQueen's UniversityPolytechnique MontréalUniversity of SaskatchewanUniversité de MontréalUniversité LavalUniversity of OttawaMcGill UniversityUniversity of Ontario Institute of TechnologyUniversity of TorontoToronto Metropolitan UniversityUniversity of WaterlooUniversity of British ColumbiaUniversity of GuelphYork University
Fundersnot available
KeywordsComputer science

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)0.006
metaresearch head score (Gemma)0.018
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 score0.370
Threshold uncertainty score0.527

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0030.001
Scholarly communication0.0080.002
Open science0.0030.003
Research integrity0.0070.003
Insufficient payload (model declined to judge)0.6300.560

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 head0.062
GPT teacher head0.228
Teacher spread0.166 · 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
Published2020
Admission routes1
Has abstractno

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Same topicDiverse Perspectives in Modern StudiesFrench-language works237,207