Dewclaws in wolves as evidence of admixed ancestry with dogs
Bibliographic record
Abstract
Vestigial first toes (dewclaws) on the hind legs are common in large dog (Canis lupus familiaris) breeds but are absent in wild canids, including wolves (Canis lupus). Based on observational criteria, dewclaws in wolves have been generally regarded as a clue of hybridization with dogs, although this was not substantiated by molecular evidence. By means of population assignment and genetic admixture analysis, we investigated individual genotypes of three dewclawed wolves from Tuscany (central Italy, 1993–2001). Based on 18 microsatellite markers, dewclawed wolves were not uniquely assigned to the Italian wolf population but appeared to be second or later generation backcrosses of wolf–dog hybrids. Alleles uniquely shared with dogs, and mitochondrial DNA and Y haplotypes identical to those of Italian wolves, further supported their admixed ancestry. Although patterns of dewclaw inheritance in wolf–dog hybrids and backcrosses have not been ascertained, we conclude that dewclaws in wolves, when present, are a clue of admixed ancestry, probably originating in areas where large dog breeds are involved in cross-matings. Other "atypical" morphological traits (e.g., white nails, atypical color patterns or body proportions, dental anomalies) as well might be reliable clues of admixed ancestry, and they deserve careful monitoring and molecular investigation.
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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 | 0.001 | 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 | 0.001 |
| 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".