What Happened in That Pit? An Archaeozoological and GIS Approach to Study an Accumulation of Animal Carcasses at the Roman Villa of Vilauba (Catalonia)
Bibliographic record
Abstract
Some of the deposits of animal remains documented throughout prehistory and history are clearly something other than ordinary waste from meat consumption. For the Roman period and based on their characteristics, these assemblages have been classified as butchery deposits, raw material deposits, deposits created for the hygienic management and disposal of animal carcasses, or ritual deposits. However, some are difficult to classify, and the parameters that define each of them are not clear. Here, we present a unique deposit from the Roman villa of Vilauba (Catalonia). A total of 783 cattle remains were found in an irregular-shaped 187 m2 pit originally dug to extract the clay used in the construction of the villa walls around the third quarter of the 1st century AD. The application of a contextual taphonomy approach, with the integration of archaeozoological variables, stratigraphy and context, and a GIS analysis, allowed us to document the nature and formation of this singular assemblage. It consisted of the carcasses of 14 cattle individuals from which the meat had been removed to take advantage of it by preserving it. Therefore, the parameters that characterise the refuse of this activity are presented here as a baseline for other studies.
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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 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".