Bibliographic record
Abstract
Previous article FreeContributorsPDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinked InRedditEmailQR Code SectionsMoreJohn RennerIndependent Scholar, London, United KingdomQuincy NganAssistant Professor in Art History, Yale University, New Haven, CTMary Joan Winn LeithAssociate Professor and Chair of the Department of Religious Studies, Stonehill College, Easton, MAAllyson Everingham ShecklerAssistant Professor of Art History, Stonehill College, Easton, MAVictoria AddonaPostdoctoral Fellow, McGill University, Montreal, Quebec, CanadaMichael GaudioProfessor of Art History, University of Minnesota, Minneapolis, MNFátima Bethencourt PérezAssociate Professor of Art History, University of Valladolid, SpainElizabeth SimpsonProfessor Emerita, Bard Graduate Center, New York, NY Previous article DetailsFiguresReferencesCited by Source Volume 42, Number 1Fall 2022 Sponsored by the Bard Graduate Center, New York Article DOIhttps://doi.org/10.1086/724577 © 2022 Bard Graduate Center. All rights reserved.PDF download Crossref reports no articles citing this article.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".