The origin of introduced rainbow trout (<i>Oncorhynchus mykiss</i>) in the Santa Cruz River, Patagonia, Argentina, as inferred from mitochondrial DNA
Bibliographic record
Abstract
Rainbow trout (Oncorhynchus mykiss) was first introduced into Argentinean Patagonia, the southernmost region of South America, from the United States in 1904 and at present constitutes the most conspicuous freshwater fish in lakes and rivers of the region. The Santa Cruz River in Southern Patagonia is the only river in the world where a self-sustained population of introduced rainbow trout is known to have developed an anadromous run. In this study, we examined mtDNA sequence variation to identify the source of Santa Cruz River rainbow trout, providing a historical framework to interpret the processes underlying phenotypic variation and structure of Patagonian populations. The Santa Cruz River may harbor distinct North American stocks of rainbow trout, widely distributed around the world during the late 19th and early 20th centuries, but today threatened after decades of habitat loss, species introduction, and introgression from alien stocks. The mtDNA sequence data revealed that the most likely origin for wild anadromous and nonanadromous fish was the McCloud River in California. Meanwhile, a local hatchery stock, representative of rainbow trout introduced from Denmark after 1950 and widely stocked ever since throughout Patagonia, most probably originated from multiple lineages from western North America, including non-Californian populations.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".