Bibliographic record
Abstract
Many species in North America range northward and barely into southern Canada. Some of these species are classified as species at risk and afforded legal protection in Canada, yet the decision to protect these populations at the edge of their range is controversial. To determine if edge populations are more likely to be listed as at risk, fish species were grouped based on whether they are listed as at risk in Canada then assigned values for several life history and ecological traits and a discriminant function analysis was conducted. Conservation status was correctly predicted 93% of the time. Traits that predicted conservation status were endemic distribution, recognized distinct populations, edge distributions and long-lived. Northern edge populations of Spotted Gar ( Lepisosteus oculatus ) were investigated for the presence of local adaptations. Adaptations in the form of delayed age at maturity and lower body condition were seen in the Rondeau Bay population of Spotted Gar. Differences in habitat selection and offshore distance were also seen in the Rondeau Bay population when compared to southern core populations of the species. Microsatellite analyses showed that northern edge populations were divergent from southern core populations and the Rondeau Bay population carried the entirety of the genetic diversity found in the north. A phylogeny based on mitochondrial gene sequences was created and used to identify five commercially obtained gar samples. Four individuals obtained at a pet shop in Kitchener, Ontario, labeled as Spotted Gar, were identified as Florida Gar ( Lepisosteus platyrhincus ). A specimen obtained at a commercial fish market in Toronto, Ontario was identified as a Spotted Gar and likely originated from Long Point Bay, Lake Erie. The presence of local adaptation affirms the need to protect edge populations to conserve the overall diversity within the Spotted Gar and other species in Canada.
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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 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".