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2023· book-chapter· en· W4319457335 on OpenAlexaff
Yekbun Adıgüzel, Laura Andréoli, Eleonora Antonelli, Lambros Athanassiou, Panagiotis Athanassiou, Tadej Avčin, Nina Babel, Nicole Bechmann, Carina Benzvi, В. О. Бицадзе, Dimitrios P. Bogdanos, Srinivsasa Reddy Bonam, Vânia Vieira Borba, M.O. Borghi, Stefan R. Bornstein, Nicola Luigi Bragazzi, Pedro Carrera‐Bastos, Leonid P. Churilov, Francesca Crisafulli, María Pilar Cruz-Domínguez, M. Cugno, Maria Giovanna Danieli, Paula David, Tal Davidy, Silvia-Ebe-Lucia Della-Pina, Arad Dotan, Marie‐Agnès Dragon‐Durey, Georgios Efthymiou, Michael Ehrenfeld, Ismaı̈l Elalamy, Nina Emeršič, Kamaeva Evelina, Giulia Fontana, Franco Franceschini, Véronique Frémeaux‐Bacchi, Marvin J. Fritzler, María F. Galaviz-Sánchez, Ksenia Ganina, Natalia S. Gavrilova, Roberto Giacomelli, Jean‐Christophe Gris, Caroline I. Gutierrez-Melgarejo, Ehud Horwitz, Eitan Israeli, Étienne Jacotot, Luis Jara‐Palomares, Darja Kanduc, Christoph Kessel, J. Kh. Khizroeva, A. V. Kolobov, Ifigenia Kostoglou‐Athanassiou, С. В. Лапин, G. Lasagni, Aaron Lerner, Danielle Zemer Lev, Soprun Lidiia, Berenice López-Zamora, José Manuel Lozano, Abihai Lucas Hernández, А. D. Makatsariya, Анна Малкова, Lukashenko Maria, Margarita Mayorova, Gabriela Medina, P.L. Meroni, Dror Mevorach, Sylviane Muller, Н. Н. Петрова, Vladimir N. Nikolenko, Alberto Ordinola Navarro, Irvin Ordoñez-González, Alberto Paladini, M. Yu. Pervakova, Ofer Perzon, Nataliya Petrova, Marko Radic, Eirini I. Rigopoulou, Jorge-Manuel Rodrigues-Fernandes, Avi Z. Rosenberg, Piero Ruscitti, Varvara A. Ryabkova, Rafael Simone Saia, Sergey V. Sankov, Maria V. Sankova, Yehuda Shoenfeld, Mikhail Y. Sinelnikov, Полина Анатольевна Соболевская, Ulrik Stervbo, Laura Talamini, С. А. Тарасов, Lorenz Thurner, Anǵela Tincani, О. Yu. Tkachenko, M. Tocut, Francesco Ursini, Olga Vera‐Lastra, Angélica T. Vieira, Aristo Vojdani, Elroy Vojdani, ‬‬‬‬Abdulla Watad, G. Zandman-Goddard, Ofir Zmira, Daniela Noa Zohar

Bibliographic record

VenueElsevier eBooks · 2023
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsYork University
Fundersnot available
KeywordsHistoryPsychologyComputer 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)0.001
metaresearch head score (Gemma)0.006
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 score0.204
Threshold uncertainty score0.291

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
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)0.7960.763

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 head0.041
GPT teacher head0.208
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
Published2023
Admission routes1
Has abstractno

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