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2025· book-chapter· en· W7139940407 on OpenAlexaff
Rolla Abu-Arja, Jenny Adamski, Manish K. Aghi, Manmeet Singh Ahluwalia, Deborah H. Allen, Deborah H. Allen, Iyad Alnahhas, Elizabeth Alva, Nancy Ann Oberheim Bush, Sonikpreet Aulakh, Nicholas G. Avgeropoulos, Adel Azghadi, Atallah Baydoun, Bianca Bergsneider, Deborah T. Blumenthal, Éric Bouffet, Priscilla K. Brastianos, Sarah Braun, Henry Brem, William C. Broaddus, Casey B. Brown, Sebastian Bühner, Arpan R. Chakraborty, Marc C. Chamberlain, Susan Chang, Arjun Chaudhary, Zhijian Chen, Sofia Chernet, John Y. Choi, Sajeel Chowdhary, Nathan Clarke, Jennifer Cotter, Erin Crotty, Sunit Das, Girish Dhall, Karan Dixit, Richard Drexler, Gavin P. Dunn, Mahmoud Elguindy, Kevin B. Elmore, Herbert H. Engelhard, Laura Escudero, Jawad Fares, Robert A. Fenstermaker, Luís Fernández, Isabelle Ferry, Sheila Figel, Mariella G. Filbin, Karen Fink, Christina H. Fong, Maryam Fouladi, Joshua Friedman, Michael C. Frühwald, Trishla Gandhi, Yifeng Gao, Pierre Giglio, Noah Gorelick, Michael G.M. Grant, David Gritsch, Muhammet Enes Gurses, Daphne Haas-Kogan, Jan T. Hachmann, John W. Henson, Vratko Himič, Christopher G. Hubert, Mai Huynh, Eric Jackson, Marie Jaeger-Krause, Varun Jain, Tanner M. Johanns, Samuel J. Joseph, Matthias A. Karajannis, Balveen Kaur, Raminderjit Kaur, Santosh Kesari, Sara Khan, Lindsay Kilburn, Hannah Kim, Lily Kim, David King, Tiemo J. Klisch, Ricardo J. Komotar, Aiden Kong, Sergej Kudruk, Claudia M. Kuzan-Fischer, Sean S. Lau, Margot Lazow, Eudocia Q. Lee, Didier R. Lefebvre, Maciej S. Lesniak, Denise Leung, Linda M. Liau, Michael Lim, Mary Jane Lim-Fat, Catherine Lin, James K.C. Liu, Ashlee R. Loughan, Mark Malkin, Emmanuel Mantilla, Brendan J. McCullough, John M. McGregor, Hamid R. Mohtashami, Michelle Monje, Sabine Mueller, Edward A. Neuwelt, Herbert B. Newton, Antonio M Omuro, Roger Packer, Nina A. Paleologos, Hardikkumar Patel, Marta Penas-Prado, Edgar Petrosyan, Kester A. Phillips, Clement Pillainayagam, Marcos Pinho, Vivek Podder, Maleeha A. Qazi, Jeffrey J. Raizer, Prisha Ranjan, Tulika Ranjan, Scott Raskin, Raghuram Reddy, Sarah Reel, Samuele Renzi, Rebecca Ronsley, Daniel Rosen, Tom Rosenberg, James Rutka, Upasana Sahu, Ralph Salloum, John Sampson, Adrienne C. Scheck, David Schiff, Arielle Schwarzberg, Brian J. Scott, Harsh P. Shah, Sajina Shakya, Tolou Shokuhfar, Seema Shroff, Caylee Silvers, Sheila K. Singh, Hasan Slika, Lilly J. Speier, Avishay Spitzer, Michael D. Staudt, Luca Szalontay, Benita Tamrazi, Ryuma Tanaka, Shervin Taslimi, Kate E. Therkelsen, Grace Tobin, Consuelo Torrini, Hung Ngoc Tran, Betty Tyler, Rafael A. Vega, Prashant Vempati, Monica Venere, C. N. Venugopal, Javier Villanueva-Meyer, Gerald Wallace, Lixin Wan, Julia Weiner, Kyle C. Wu, Jianzhong Zhang, Peng Zhang

Bibliographic record

VenueElsevier eBooks · 2025
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsHamilton Health SciencesUniversity of TorontoQueen's UniversityMcMaster UniversityUniversité LavalHospital for Sick Children
Fundersnot available
Keywordsnot available

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)0.005
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 score0.202
Threshold uncertainty score0.288

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.005
Science and technology studies0.0020.000
Scholarly communication0.0050.004
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.7980.763

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 head0.023
GPT teacher head0.202
Teacher spread0.178 · 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
Published2025
Admission routes1
Has abstractno

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