Molecular markers in keratins from Mysticeti whales for species identification of baleen in museum and archaeological collections
Bibliographic record
Abstract
Baleen has been harvested by indigenous people for thousands of years, as well as collected by whalers as an additional product of commercial whaling in modern times. Baleen refers to the food-filtering system of Mysticeti whales; a full baleen rack consists of dozens of plates of a tough and flexible keratinous material that terminate in bristles. Due to its properties, baleen was a valuable raw material used in a wide range of artefacts, from implements to clothing. Baleen is not widely used today, however, analyses of this biomolecular tissue have the potential to contribute to conservation efforts, studies of genetic diversity and a better understanding of the exploitation and use of Mysticeti whales in past and recent times. Fortunately, baleen is present in abundance in museum natural history collections. However, it is often difficult or impossible to make a species identification of manufactured or old baleen. Here, we propose a new tool for biomolecular identification of baleen based on its main structural component alpha-keratin (the same protein that makes up hair and fingernails). With the exception of minke whales, alpha-keratin sequences are not yet known for baleen whales. We therefore used peptide mass fingerprinting to determine peptidic profiles in well documented baleen and evaluated the possibility of using this technique to differentiate species in baleen samples that are not adequately identified or are unidentified. We examined baleen from ten different species of whales and determined molecular markers for each species, including species-specific markers. In the case of the Bryde's whales, differences between specimens suggest distinct species or sub-species, consistent with the complex phylogeny of the species. Finally, the methodology was applied to 29 fragments of baleen excavated from archaeological sites in Labrador, Canada (representing 1500 years of whale use by prehistoric people), demonstrating a dominance of bowhead whale (Balaena mysticetus) in the archaeological assemblage and the successful application of the peptide mass fingerprinting technique to identify the species of whale in unidentified and partially degraded samples.
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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 | 0.001 | 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".