Paleopathology, Entheseal Changes, and Cross-Sectional Geometry: The Zooarchaeology of Working Animals
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Morphological changes in the skeletons of working animals such as reindeer, horse, and cattle have long been observed and documented in the archaeological record. Activities such as riding, carrying cargo on their backs, and pulling vehicles like sleds and ploughs throughout an animal’s life history cause alterations and variations to skeletal tissue. Such alterations include paleopathological lesions, entheseal changes (EC)—alterations in muscle, tendon, and ligament attachment sites on bone—and variations in cross-sectional bone geometry (CSBG). These clues are helpful for reconstructing human-animal relationships in faunal remains of our archaeological past. However, other factors influence the morphological appearance of skeletal tissue besides working activities, such as age, sex, body size, nutrition, genetics, environmental factors, and management by human caretakers. This article explores how paleopathological lesions, EC, and CSBG in faunal skeletal remains are examined to reconstruct working activity and changes to human-animal relationships in the archaeological record. In particular, we discuss two primary topics of inquiry: (1) a review of paleopathological identifiers in working animals such as cattle, horse, camel, and reindeer; and (2) how EC and CSBG are understood in terms of bone functional adaptation, and their application in working and non-working animals such as reindeer and horse. Next, we analyze each topic highlighting their benefits and limitations, including how they contribute to archeological understandings of human-animal relationships in the past, as well as their implications for future research.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.002 | 0.026 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 it