Hierarchical patterns of population structure in the endangered Fraser River white sturgeon (<i>Acipenser transmontanus</i>) and implications for conservation
Bibliographic record
Abstract
The Fraser River system consists of five white sturgeon (Acipenser transmontanus) management units, two of which are listed as endangered populations under Canada’s Species at Risk Act. The delineation of these management units was based primarily on population genetic analysis with samples parsed by collection location. We used polysomic microsatellite markers to examine population structure in the Fraser River system with samples parsed by collection location and with a genetic clustering algorithm. Strong levels of genetic divergence were revealed above and below Hells Gate, a narrowing of the Fraser canyon further obstructed by a rockslide in 1913. Additional analyses revealed population substructure on the Fraser River above Hells Gate. The Middle Fraser River (SG-3) and Nechako River were found to be distinct populations, while the Upper Fraser River, although currently listed as an endangered population, represented a mixing area for white sturgeon originating from SG-3 and Nechako. Differences between these results and previous genetic investigations may be attributed to the detection of population mixing when genetic clustering is used to infer population structure.
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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 | 0.000 | 0.001 |
| 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".