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Contributors

2024· book-chapter· en· W4400134484 on OpenAlexaff
Marjorie Abalos, Suad Hashim Ahmed, Reem Al Hammadi, Asma Al Obeidli, Hussain Abdul Rahman Al Rand, Ola Aldafrawy, Alia Mohammad Rafi Aldallal, Saqr Alhemeiri, Aisha Alhouti, Dari Alhuwail, Paula Aljovin, Pedro Altungy, Tina C. Ambos, Taavi Annus, Logan Ansell, Maxwell Antwi, Alex Israel Attachey, Rifat Atun, Sulzhan Bali, Erin S. Barry, Daniela Bas, Christoph Benn, Sripriya Bikkani, Nicole K. Bulanchuk, Craig Burgess, Bo Cao, M Claeson, Christiaan Coetzee, Patrick F. Connolly, Jennifer Crouch, L.T. Cunningham, Marija Davcheva, Juan Ramón De La Fuente, Meredith del Pilar-Labarda, Florence L. Denmark, Madhu Deshmukh, Deepika Devadas, Roopa Dhatt, Daniella Diaz, Omar ElFata, Pauline Eluère, Kameshwar Eranki, Temitayo Erogbogbo, Satoshi Ezoe, Erin K. Ferenchick, Rafael Figueroa, Brianna Fitapelli, Nathaniel Foote, Cameron Fox, Maria Inês Francisco Viva, Christian Garbe, Beatrice Gatumia, Kamal Gautam, Amandeep S. Gill, Lasha Goguadze, Andrew J. Greenshaw, Russell Greiner, Monique Arantes Guimarães, Aline Guzik, Nadine Hachach-Haram, Ann Herrmann-Nehdi, Taylor Hirschberg, Matthew Hughsam, Geoffrey Ibbotson, Tara Imalingat, Maria Isabel Iñigo Petralanda, Kiyan Irani, Biju Jacob, Zsuzsanna Jakab, Gillian Javetski, Preethi John, Mutahi Kagwe, Pradeep Kakkattil, Mwenya Kasonde, Kanishka Katara, Shariha Khanam Khalid, Sadikchhya Khanal, Rana Khazbak, Eva Kiegele, Sarah Kline, J Knox, Pitambar Koirala, Rotem Kopel, Eneyi E. Kpokiri, Suresh Kumar, Judy Kuriansky, Erica Layer, Tao Li, Sara Liébana, Hanna Lissinna, Sonia Livingstone, David D. Luxton, Catherine Machalaba, Haifa Madi, Carthi Mannikarottu, Cherisse Mark, Patricio V. Marquez, Stéphanie Racine Maurice, Anita M. McGahan, Patricia Mechael, Tanya Mehdizadeh, Sylvia Paola Mendoza, Kertti Merimaa, Tahila Mintz, Nomtika Mjwana, Taylor Mulligan-Stark, Vivek Nair, Jasmine M. Noble, Mohammed Nurhussein, Ian O’Donnell, Patty O’Hayer, Werner Obermeyer, Zerin Osho, Daniel Otzoy-García, Amanda Pain, Mauro Pantaleo, Muhammad Ali Pate, William C. Philbrick, Geetha Krishnan Gopalakrishna Pillai, Ashley Porto, Girish Ramachandran, Nithya Ramanathan, Onisoa Rindra-Ralidera, Fatima Rizwan, Erin Ross, Robert Ross, Rajeev Sadanandan, Rayna Sadia, James Sale, Udani Samarasekera, Sujay Santra, Jagjeet Sareen, Shekhar Saxena, Daniel Schaudel, Katherine Semrau, Rahul Sharma, Shannon Shibata-Germanos, Zara Shubber, Megha Siddhanta, Patrik Silborn, Moitreyee Sinha, Sylvana Q. Sinha, Mehdi Snène, Anna Stauber, Mariya Stoilova, Joe Stringer, Jie Sui, Ashraf Swidan, Reem Talhouk, Manal Mohamed Omran Taryam, Katherine Tatarinov, Jami Taylor, Anil Thapliyal, Annie Thériault, Rachel Thompson, Katlen Tillman, Anand Tiwari, John Torous, Joseph D. Tucker, Gabe Twose, Joost van Engen, John Varallo, Carlos Velo, Akarsh Venkatasubramanian, Dominique Vervoort, Sidique Wai, David Wallerstein, Rispah J Walumbe, Waruguru Wanjau, Eleanor Watson, Dasoo Milton Yoon, Lian Zeitz, Feng Zhao

Bibliographic record

VenueElsevier eBooks · 2024
Typebook-chapter
Languageen
Field
Topic
Canadian institutionsReach Technologies (Canada)
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)0.000
metaresearch head score (Gemma)0.002
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 score0.256
Threshold uncertainty score0.365

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0020.001
Scholarly communication0.0060.004
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.7440.680

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 head0.015
GPT teacher head0.248
Teacher spread0.233 · 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
Published2024
Admission routes1
Has abstractno

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