Identifying the unidentified fauna enhances insights into hominin subsistence strategies during the Middle to Upper Palaeolithic transition
Bibliographic record
Abstract
Abstract Understanding Palaeolithic hominin subsistence strategies requires the comprehensive taxonomic identification of faunal remains. The high fragmentation of Late Pleistocene faunal assemblages often prevents proper taxonomic identification based on bone morphology. It has been assumed that the morphologically unidentifiable component of the faunal assemblage would reflect the taxonomic abundances of the morphologically identified portion. In this study, we analyse three faunal datasets covering the Middle to Upper Palaeolithic transition (MUPT) at Bacho Kiro Cave (Bulgaria) and Les Cottés and La Ferrassie (France) with the application of collagen type I peptide mass fingerprinting (ZooMS). Our results emphasise that the fragmented component of Palaeolithic bone assemblages can differ significantly from the morphologically identifiable component. We obtain contrasting identification rates between taxa resulting in an overrepresentation of morphologically identified reindeer ( Rangifer tarandus ) and an underrepresentation of aurochs/bison ( Bos/Bison) and horse/European ass ( Equus ) at Les Cottés and La Ferrassie. Together with an increase in the relative diversity of the faunal composition, these results have implications for the interpretation of subsistence strategies during a period of possible interaction between Neanderthals and Homo sapiens in Europe. Furthermore, shifts in faunal community composition and in carnivore activity suggest a change in the interaction between humans and carnivores across the MUPT and indicate a possible difference in site use between Neanderthals and Homo sapiens . The combined use of traditional and biomolecular methods allows (zoo)archaeologists to tackle some of the methodological limits commonly faced during the morphological assessment of Palaeolithic bone assemblages.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.007 | 0.027 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; 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".