Bibliographic record
Abstract
Introduction Understanding the ecological attributes of extinct organisms has long been a major research topic in paleobiology, dating back to the pioneering work of the French paleontologist Georges Cuvier in the early nineteenth century. Inferences concerning the ecology of an extinct organism can be based on functional interpretation of its structure, by analogy with present-day relatives, or from the sedimentary context and distribution of fossil remains referable to this taxon (Wing et al . 1992). Traditionally, functional morphology has been the most widely used of these approaches. It basically relies on the analysis of organisms as simple machines with functional attributes that can be inferred from the physical properties of their bodies as well as from their shape and size. Chemical analyses of hard tissues (such as extraction of preserved stable carbon isotopes) increasingly are providing significant new data for inferring diet in extinct animals. In recent years, researchers have developed various procedures for linking inferences concerning function in fossils to phylogenetic analyses, increasing confidence in the robustness of these reconstructions (see various papers in Thomason [1995]). Herbivory, the consumption of plant tissues, is a widespread phenomenon among terrestrial vertebrates. It has frequently and independently evolved in many lineages of amniotes during the last 300 million years or so. Some major groups of herbivorous tetrapods, such as ungulate mammals and ornithischian dinosaurs, attained great abundance and taxonomic diversity. Indeed, the advent of herbivory among land-dwelling tetrapods was one of the key events in the history of life on land.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.008 |
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".