The prelude to industrial whaling: identifying the targets of ancient European whaling using zooarchaeology and collagen mass-peptide fingerprinting
Bibliographic record
Abstract
Taxonomic identification of whale bones found during archaeological excavations is problematic due to their typically fragmented state. This difficulty limits understanding of both the past spatio-temporal distributions of whale populations and of possible early whaling activities. To overcome this challenge, we performed zooarchaeology by mass spectrometry on an unprecedented 719 archaeological and palaeontological specimens of probable whale bone from Atlantic European contexts, predominantly dating from ca 3500 BCE to the eighteenth century CE. The results show high numbers of Balaenidae (many probably North Atlantic right whale ( Eubalaena glacialis )) and grey whale ( Eschrichtius robustus ) specimens, two taxa no longer present in the eastern North Atlantic. This discovery matches expectations regarding the past utilization of North Atlantic right whales, but was unanticipated for grey whales, which have hitherto rarely been identified in the European zooarchaeological record. Many of these specimens derive from contexts associated with mediaeval cultures frequently linked to whaling: the Basques, northern Spaniards, Normans, Flemish, Frisians, Anglo-Saxons and Scandinavians. This association raises the likelihood that early whaling impacted these taxa, contributing to their extirpation and extinction. Much lower numbers of other large cetacean taxa were identified, suggesting that what are now the most depleted whales were once those most frequently used.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".