The Rise of placental mammals: origins and relationships of the major extant clades
Bibliographic record
Abstract
From shrews to blue whales, placental mammals are among the most diverse and successful vertebrates on the Earth. Arising sometime near the Late Cretaceous, this broad clade of mammals contains more than 1,000 genera and approximately 4,400 extant species. Although much studied, the origin and diversification of the placentals continue to be a source of debate. Paleontologists Kenneth D. Rose and J. David Archibald have assembled the world's leading authorities to provide a comprehensive and up-to-date evolutionary history of placental mammals. Focusing on anatomical evidence, the contributors present an unbiased scientific account of the initial radiation and ordinal relationships of placental mammals, representing both the consensus and significant minority viewpoints. This book will be invaluable to paleontologists, evolutionary biologists, mammalogists, and students. Contributors: J. David Archibald, San Diego State University; Robert J. Asher, Institut fur Systematische Zoologie; Jonathan I. Bloch, University of Michigan; Douglas M. Boyer, University of Michigan; Daryl P. Domning, Howard University; Eduardo Eizirik, National Cancer Institute; Robert J. Emry, Smithsonian Institution; Jorg Erfurt, Martin-Luther-University; John J. Flynn, The Field Museum; Timothy J. Gaudin, University of Tennessee; Emmanuel Gheerbrant, Museum National d'Histoire Naturelle; Philip D. Gingerich, The University of Michigan; Patricia A. Holroyd, University of California, Berkeley; J. J. Hooker, The Natural History Museum; Leo F. Laporte, University of California, Santa Cruz; Jin Meng, American Museum of Natural History;William J. Murphy, National Cancer Institute; Jason C. Mussell, The Johns Hopkins University School of Medicine; Michael J. Novacek, American Museum of Natural History; Stephen J. O'Brien, National Cancer Institute; Kenneth D. Rose, The Johns Hopkins University School of Medicine; Guillermo W. Rougier, University of Louisville; Eric J. Sargis, Yale University; Mary T. Silcox, University of Winnipeg; Nancy B. Simmons, American Museum of Natural History; Mark S. Springer, University of California, Riverside; Gerhard Storch, Forschungsinstitut Senckenberg; Pascal Tassy, Museum National d'Histoire Naturelle; Jessica M. Theodor, Illinois State Museum; Gina D. Wesley, The University of Chicago; John R. Wible, Carnegie Museum of Natural History; Andre Wyss, University of California, Santa Barbara.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".