Bibliographic record
Abstract
We thank Jorge Sequeira (Museu Geol\u00F3gico, Laborat\u00F3rio Nacional de Energia e Geologia, Lisbon, Portugal) and Museu Geol\u00F3gico de Lisboa for providing the access to the Guimarota collection; Mariana Valente (NOVA School of Science and Technology, Lisbon, Portugal) for the help in cataloguing the specimens from Guimarota, allowing to locate the new relevant material; and Susan Evans (Cell & Developmental Biology, University College London, London, UK) for her help in understanding the anatomy of both animals. We are grateful to both reviewers, Susan Evans and John Foster (Utah Field House of Natural History State Park Museum, Vernal, USA), for providing insightful comments and suggestions to improve the manuscript. ARDG wants to thank Matthew Carrano (Smithsonian National Museum of Natural History, Washington, USA), Daniel Brinkman and Vanessa Rhue (both Yale Peabody Museum of Natural History, New Haven, USA), Howard Gibbins and Michael Cadwell (both University of Alberta Laboratory of Vertebrate Palaeontology, Edmonton, Canada) and James Gardner (Royal Tyrell Museum of Palaeontology, Drumheller, Canada) for granting access to comparative material; as well as Anabela Veiga (Escola Superior de Tecnologia e Gest\u00E3o of the Polit\u00E9cnico de Leiria, Portugal) and the Museu de Leiria to facilitate access to the Guimarota mine and give global context of the excavation. Project PID2021-122612OB-I00, funded by MCIN/AEI/10.13039/501100011033; Grant RYC2021-034473-I funded by MCIN/AEI/10.13039/501100011033 and by the European Union \u201CNext Generation EU\u201D/PRTR\u201D; and by the Aragon Regional Government (Grupo de referencia: E18_23R Aragosaurus: Recursos Geol\u00F3gicos y Paleoambientales). EPP was supported by a postdoctoral contract (Mar\u00EDa Zambrano) funded by the Ministry of Universities of the Government of Spain through the Next Generation EU funds of the European Union. Publisher Copyright: Copyright © 2025 A.R.D. Guillaume et al.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".