The category-modifier system: a hierarchical classification scheme for vertebrate tooth marks
Bibliographic record
Abstract
Abstract Preserved records of tooth–bone interactions, known as tooth marks, can yield a wealth of information regarding organismal behavior and ecology. For this reason, workers in a wide range of disciplines, but particularly paleontology, have inspected and interpreted these features for decades. Although previous studies have gleaned invaluable insights, they have also described tooth marks using terminological frameworks that have been incompletely defined, have incorporated behavioral hypotheses in definitions, and/or have been inconsistently applied. To address these problems, we introduce the category-modifier (CM) system, the first system to both sort tooth marks into clearly defined main categories and use descriptive modifiers to characterize their appearance more precisely. The CM system is designed to apply to a wide range of vertebrates, to enable comparisons across disciplines and studies, and to help researchers keep their investigations into behavioral hypotheses free of circular reasoning.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".