Population genetic assessment of Inconnu (Stenodus leucichthys) in the Northwest Territories
Bibliographic record
Abstract
Inconnu (Stenodus leucichthys) in Great Slave Lake (GSL), NT have been over-fished resulting in declines in some stocks. By characterizing the population genetics of fish in this area, management can better understand how over-exploitation and other factors affect stocks and use this knowledge to inform their monitoring strategies. Nearly 1000 tissue samples were collected throughout their geographic range in NT from 1988-2017. Population genetic analyses with 17 microsatellite markers were performed to determine the influence of geography, post-glacial colonization, and philopatry on the genetic diversity and structure of Inconnu in NT. Geographic distance significantly affected the genetic differentiation of Inconnu. Significantly lower genetic diversity was observed in GSL populations compared to fish from the upper/lower Mackenzie River region due to post-glacial colonization. Genetic structuring was detected among Inconnu stocks associated with particular river systems suggesting philopatric behaviour. River sampling is critical to understanding the genetic dynamics of Inconnu in GSL.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".