Species identification of Australian marsupials using collagen fingerprinting
Bibliographic record
Abstract
The study of faunal remains from archaeological sites is often complicated by the presence of large numbers of highly fragmented, morphologically unidentifiable bones. In Australia, this is the combined result of harsh preservation conditions and frequent scavenging by marsupial carnivores. The collagen fingerprinting method known as zooarchaeology by mass spectrometry (ZooMS) offers a means to address these challenges and improve identification rates of fragmented bones. Here, we present novel ZooMS peptide markers for 24 extant marsupial and monotreme species that allow for genus-level distinctions between these species. We demonstrate the utility of these new peptide markers by using them to taxonomically identify bone fragments from a nineteenth-century colonial-era pearlshell fishery at Bandicoot Bay, Barrow Island. The suite of peptide biomarkers presented in this study, which focus on a range of ecologically and culturally important species, have the potential to significantly amplify the zooarchaeological and paleontological record of Australia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".