Factors affecting the survival of Chinook salmon (<i>Oncorhynchus tshawytscha</i>) embryos in upper and middle Columbia River watersheds, Washington State, USA
Bibliographic record
Abstract
Greater understanding of environmental effects to salmon survival during incubation can aid in prediction and facilitate population modeling at local and regional scales. Four basin-scale studies of Chinook salmon egg-to-fry survival were conducted between years 2009 and 2021 in spawning tributaries of the upper and middle Columbia River. Each of the four basins support Chinook salmon populations that are either currently hatchery-supplemented or have a recent history of supplementation, and most are listed under the U.S. Endangered Species Act. Together, these studies provided a unique opportunity to assess factors influential to egg-to-fry survival, such as fine sediment infiltration and substrate scour, in the context of differences in survival among rivers and study years. We detected a 16.8% decrease in the odds of survival for every 1 cm increase in substrate scour, a 1.0% decrease in the survival odds with each one-unit change in the percentage of accumulated fines, distinct differences in survival within and among rivers (from 30.5% to 82.5%), and subtle effects of parentage in the presence of environmental factors. The causal and predictive relationships provided here will inform conservation, restoration, and further research.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".