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2021· article· en· W4207054236 on OpenAlexaff
Huber Nieto–Chaupis, Chenguang Xiao, Shuo Wang, Majid Soheili, Maryam Amir Haeri, Mohammad Askarizadeh, Abolfazl Javidian, Masoumeh Zare, Kim Nguyen, Chih-Lin Chang, Shiou-Chi Li, Jen-Wei Huang, Adham Salih, Amiram Moshaiov, Longcan Chen, Meng Pang, Hisao Ishibuchi, Ke Shang, Felipe Honjo Ide, Hernán Aguirre, Darrell Whitley, Cheng Gong, Liewen Pang, Mahrokh Javadi, Sanaz Mostaghim, Sahil Datta, J. Holmberg, Elena Antonova, Chun-Shu Wei, National Yang, Ming Tung, Gang Li, Onuoha Ogechi, Michaela Mark, B. Stephen, Chao Chen, Philipp Frank, Campbell Gorman, Yu–Kai Wang, Inês Domingos, Guang‐Zhong Yang, Fani Deligianni, Ivan Shpurov, Tom Froese, Jared Mejia, Christiana Marchese, Oliver Chang, Anthony J. Clark, Ehsan Bojnordi, Jalaleddin Mousavirad, Gerald Schaefer, Iakov Korovin, Raphael Patrick Prager, Vinzent Moritz, Heike Seiler, Pascal Trautmann, Richmond Asiedu Agyapong, Mahmoud Nabil, Abdul-Rauf Nuhu, Mushahid I. Rasul, Abdollah Homaifar, Stefano Iannucci, Emiliano Casalicchio, Matteo Lucantonio, Chihiro Watanabe, Taiji Suzuki, Pei-Yi Hao, Jaeyoon Lee, Hyuntak Lim, Ki‐Seok Chung, Charlie Veal, Marshall B. Lindsay, Scott D. Kovaleski, Derek T. Anderson

Bibliographic record

Venue2021 IEEE Symposium Series on Computational Intelligence (SSCI) · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsÉcole de Technologie SupérieureUniversité de Montréal
Fundersnot available
KeywordsTable (database)Computer scienceDatabase

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)0.001
metaresearch head score (Gemma)0.007
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 score0.120
Threshold uncertainty score0.171

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0020.000
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.8800.841

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 head0.053
GPT teacher head0.241
Teacher spread0.188 · 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".

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Citations0
Published2021
Admission routes1
Has abstractno

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