Transactions of the American Fisheries Society 131:1093–1105, 2002 � Copyright by the American Fisheries Society 2002 Genetic Structure of Columbia River Redband Trout Populations in the Kootenai River Drainage, Montana, Revealed by Microsatellite and All
Bibliographic record
Abstract
Abstract. — We describe the genetic divergence among 10 populations of redband trout Onco rhynchus mykiss gairdneri from the upper Columbia River drainage. Resident redband trout from two watersheds in the Kootenai River drainage and hatchery stocks of migratory Kamloops redband trout from Kootenay Lake, British Columbia, were analyzed using allele frequency data from microsatellite and allozyme loci. The Kamloops populations have significantly different allele frequencies from those of the Kootenai River drainage. Of the total genetic variation detected in the resident redband trout, 40.7 % (microsatellites) and 15.5 % (allozymes) were due to differences between populations from the two Kootenai River watersheds. The divergence among populations within each watershed, however, was less than 3.5 % with both techniques. Our data indicate that watershed-specific broodstocks of redband trout are needed by fisheries managers for reintroduction or the supplementation of populations at risk of extinction. The Columbia River redband trout Oncorhyn- that the range of redband trout in the upper Co chus mykiss gairdneri, a subspecies of rainbow lumbia River basin extends into northwestern trout O. mykiss, is native to the Fraser and Colum- Montana to at least the Kootenai River barrier falls bia River drainages east of the Cascade Mountain (Figure 1). The allele frequencies of 95 popula
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.277 | 0.163 |
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".