Collagen fingerprinting traces the introduction of caprines to island Eastern Africa
Bibliographic record
Abstract
The human colonization of eastern Africa's near- and offshore islands was accompanied by the translocation of several domestic, wild and commensal fauna, many of which had long-term impacts on local environments. To better understand the timing and nature of the introduction of domesticated caprines (sheep and goat) to these islands, this study applied collagen peptide fingerprinting (Zooarchaeology by Mass Spectrometry or ZooMS) to archaeological remains from eight Iron Age sites, dating betweenca300 and 1000 CE, in the Zanzibar, Mafia and Comoros archipelagos. Where previous zooarchaeological analyses had identified caprine remains at four of these sites, this study identified goat at seven sites and sheep at three, demonstrating that caprines were more widespread than previously known. The ZooMS results support an introduction of goats to island eastern Africa from at least the seventh century CE, while sheep in our sample arrived one–two centuries later. Goats may have been preferred because, as browsers, they were better adapted to the islands' environments. The results allow for a more accurate understanding of early caprine husbandry in the study region and provide a critical archaeological baseline for examining the potential long-term impacts of translocated fauna on island ecologies.
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.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".