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2011· book-chapter· en· W4251375862 on OpenAlexaff
Margaret Adams, Manoj Aggarwal, Tausif Ahmed, Patrick Allard, Arturo Anadón, G Anger, Anthony E. Archibong, Michael Aschner, Daiana Silva Ávila, Debasis Bagchi, Manashi Bagchi, Norman J. Barlow, Dana Boyd Barr, Sudheer Beedanagari, Karyn Bischoff, William M. Bracken, Rich M. Breyer, Susan Bright, Kaylon L. Bruner‐Tran, Shilpa Buch, Brian Buckley, Steven J. Bursian, Edward W. Carney, V. Castellano, Sudipta Chakraborty, Jing Chen, Sanika Chirwa, Rajani Choudhuri, Supratim Choudhuri, Jane K. Cleal, Mónica P. Colaiácovo, Robert W. Coppock, Lucio G. Costa, Maged M. Costantine, Tirupapuliyur V. Damodaran, Rosane Souza da Silva, T. Zane Davis, Marta Di Carlo, John D. Doherty, José L. Domingo, Margitta Dziwenka, Per Eriksson, Carmen Estevan Martínez, Timothy J. Evans, Bengt Fadeel, Ali S. Faqi, Marcelo Farina, Suzanne E. Fenton, Maureen H. Feuston, John Flaskos, S.J.S. Flora, Vekataseshu K. Ganjam, Dale R. Gardner, Ramesh C. Garg, Vincent F. Garry, Janee Gelineau‐van Waes, Gennaro Giordano, Scott Glaberman, Keith M. Godfrey, Marina Guizzetti, Kavita Gulati, Mary Gulumian, P.K. Gupta, Ramesh C. Gupta, Sharon M. Gwaltney‐Brant, Jeffery O. Hall, Xiaodong Han, Deborah K. Hansen, Alan J. Hargreaves, Alan M. Hoberman, Darryl B. Hood, Karin Sørig ­Hougaard, Amy L. Inselman, William Irwin, Valerian E. Kagan, Starling Kalpana, Anumantha G. Kanthasamy, Arthi Kanthasamy, Vesa Karttunen, Habibeh Khoshbouei, Hyung Sik Kim, Prasada Rao S. Kodavanti, Katarina Koprivšek, Duško Kozić, Kannan M. Krishnan, Shaila Kulkarni, Maria Kummu, Byung Mu Lee, Rohan M. Lewis, Dongmei Li, Xin Li, Marja-Liisa Lindbohm, Jarkko Loikkanen, Jan L. Lyche, Robert C. MacPhail, Brinda Mahadevan, Susan L. Makris, Jitendra K. Malik, María Rosa Martínez-Larrañaga, Jerrold S. Meyer, Dejan Milatović, Thomas J. Montine, Inbal Mor, Michelle S. Mostrom, Päivi Myllynen, Jayaprakash Narayana Kolla, Tultul Nayyar, John L. Newsted, Mingwei Ni, Efstathios Nikolaidis, Aleksandra Novakov Mikić, Meliton N. Novilla, Kevin G. Osteen, Vidhu Pachauri, Stephanie Padilla, Carlos M. Palmeira, David Pamies, Kip E. Panter, Heidi Partanen, Sangeeta Patel, Brian J. Piper, Micheline Piquette‐Miller, Vadim V. Popov, M. Margaret Pratt, G. A. Protasova, João Ramalho‐Santos, Aramandla Ramesh, Eva Álvarez Ramos, Arunabha Ray, Kausik K. Ray, Stephen J. Renaud, Bashir M. Rezk, Ronald T. Riley, Drucilla J. Roberts, Noemí Robles, João Batista Teixeira da Rocha, Rongzhu Lu, Josefa Sabrià, Magdalini Sachana, Markku Sallmén, Ana Paula Marreilha dos Santos, Kai Savolainen, Geetu Saxena, Manu Sebastian, Helmut Segner, K. Sengupta, Kathleen T. Shiverick, Elina Sieppi, Suresh C. Sikka, Michael J. Soares, Miguel Á. Sogorb, Offie P. Soldin, Chunjuan Song, Hermona Soreq, Tammy E. Stoker, Teruo Sugawara, David T. Szabo, Helena Taskinen, Peter Truran, Kirsi Vähäkangas, Subrahmanyam Vangala, Neil Vargesson, Jenni Veid, Henrik Viberg, Eugenio Vilanova, Kenneth A. Voss, Suryanarayana V. Vulimiri, Etsuko Wada, Keiji Wãda, Pralhad Wangikar, Kevin D. Welch, Honghong Yao, Zhaobao Yin, Xiaoyou Ying, Shirley Zafra‐Stone, Snjezana Zaja‐Milatovic, Matthew J. Zwiernik

Bibliographic record

VenueElsevier eBooks · 2011
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHistoryComputer scienceMedicine

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 score0.217
Threshold uncertainty score0.309

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)0.7830.746

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 head0.195
Teacher spread0.154 · 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
Published2011
Admission routes1
Has abstractno

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