Bibliographic record
Abstract
The taxonomic identity of the historical and current wolf ( Canis lupus L., 1758 or Canis lycaon Schreber, 1775 or their hybrids) population in Minnesota (MN) and the Great Lakes region has been, and continues to be, controversial. So too does its legal status under the U.S. Endangered Species Act. This review summarizes the morphological and genetic information about that population and concludes that historically the MN population consisted of a gray wolf (C. lupus) in the west and an eastern type ( Canis lupus lycaon or C. lycaon) in the east with intergrades or hybrids between the two in most of the state. After extirpation in much of its original MN range, the now-recovered population was infused with gray wolves from Ontario but still consists of hybrid lycaon × gray wolves, probably with higher content gray wolves in the west and higher content lycaon in the east but with most wolves morphologically appearing to be gray wolves. Because the current Wisconsin and Michigan wolf population was derived from MN wolves, they would be primarily hybrids as well. Future research should seek to relate genetic data with morphological measurements in MN wolves. In addition, attempts to breed coyotes ( Canis latrans Say, 1823) with gray wolves in captivity would shed considerable light on the controversy over the origin and taxonomic identity of the newly proposed C. lycaon.
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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 | 0.002 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".