Bibliographic record
Abstract
Illustrations General Editors' Preface Introduction Elizabeth Foyster, University of Cambridge, UK and James Marten, University of Milwaukee, USA 1 Family Relationships Joanne Bailey, Oxford Brookes University, UK 2 Community Alysa Levene, Oxford Brookes University, UK 3 Economy Deborah Simonton, University of Southern Denmark, Denmark 4 Geography and the Environment Giorgio Riello, University of Warwick, UK 5 Education Valentina K. Tikoff, DePaul University in Chicago, USA 6 Life Cycle Mary Abbott, Anglia Ruskin University, UK 7 The State Steven King, University of Leicester, UK 8 Faith and Religion Allison P. Coudert, University of California Davis, USA 9 Health and Science Mary Lindemann, University of Miami, USA 10 World Contexts Adriana Silvia Benzaquen, Mount Saint Vincent University, Canada Notes Bibliography Contributors Index
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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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".