No Kidding! Analysis of Leather from the Roman Fort of Vindolanda, UK.
Bibliographic record
Abstract
The Roman fort at Vindolanda on the northern frontier in Britain has produced the largest assemblage of archaeological leather from anywhere in the Roman empire. The assemblage spans over 200 years of occupation and includes numerous different types of artefacts, offering an excellent opportunity to examine the characteristics of leather used in manufacturing in the Roman period. This oral presentation presents the preliminary analysis of the animal species used for tents panels and scraps from manufacturing practices. Using ZooMS analysis, we provide results for the determination of species used for Roman tent panels and scraps. Preliminary work shows a much higher reliance on cattle and sheep hides rather than goat hides. For example: eight panels from the same tent dating to the first period of occupation at Vindolanda (ca. 85-90 CE); three panels were made from cattle hide and five came from sheep hide. These preliminary results contribute to understanding of the Roman economy on the frontier and animal species used in Roman leather manufacturing.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".