Ride, Ride, Ride, Let It Ride: Pathological Lesions in Horse Skeletons Related to Riding.
Bibliographic record
Abstract
The last 30 years have seen researchers working towards determining the earliest date of domestication for the horse (E. caballus), using osteological and pathological changes to a horse’s skeleton to infer evidence for riding—a key signature of domestication. This article provides an investigation and evaluation of the methods used, testing them on the skeletal remains of 12 horses of unknown provenience and history from Alberta, Canada. These methods include studies on the skull (cranium and mandible), the dentition (teeth), the spine, and the metapodials (lower leg bones). Overall, three of the horses exhibit osteological changes consistent with riding, three have ambiguous results, and the remaining six do not show sufficient changes. The limitations of the methods, the collections, and those of the researcher, are discussed in relation to the findings.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.015 |
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; both teacher heads agree on what is shown here.
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".