Supplementary Figure 2 - Cunanan et al., AJP Renal
Bibliographic record
Abstract
Manuscript title: Mice with a Pax2 missense variant display impaired glomerular repairAuthors: Joanna Cunanan1,2,3, Sarada Sriya Rajyam1,2,3, Bedra Sharif1,2, Khalil Udwan1,2,4, Akanchaya Rana1,2,3, Vanessa De Gregorio1,2,3, Samantha Ricardo1,2,3, Andrew Elia5, Brian Brooks6, Astrid Weins7, Martin Pollak8, Rohan John4, Moumita Barua1,2,3,91Division of Nephrology, University Health Network, Toronto ON, Canada2Toronto General Hospital Research Institute, Toronto General Hospital, Toronto ON, Canada3Institute of Medical Sciences, University of Toronto, Toronto ON, Canada4Department of Pathology, Toronto General Hospital, University of Toronto, Toronto ON, Canada5Department of Pathology, Princess Margaret Hospital, Toronto ON, Canada6Ophthalmic Genetics and Visual Function Branch, National Eye Institute, National Institutes of Health, Bethesda, MD, USA7Department of Pathology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA8Division of Nephrology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA9Temerty Faculty of Medicine, University of Toronto, Toronto ON, Canada Journal: Americal Journal of Physiology - Renal Physiology (AJP Renal)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.652 | 0.191 |
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 source (direct Gemma or distilled Codex), 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".