Characterizing the Juvenile Fish Community in Turbid Alaskan Rivers to Assess Potential Interactions with Hydrokinetic Devices
Bibliographic record
Abstract
Abstract Installation of hydrokinetic power‐generating devices is currently being considered for the Yukon and Tanana rivers, two large and glacially turbid rivers in Alaska. We sampled downstream‐migrating fish along the margins of both rivers, a middle island in the Yukon River, and mid‐channel in the Tanana River in order to assess the temporal and spatial patterns of movement by resident and anadromous fishes and hence the potential for fish interactions with hydrokinetic devices. Results suggest that (1) river margins in the Yukon and Tanana rivers are primarily utilized by resident freshwater species, (2) the mid‐channel is utilized by Pacific salmon Oncorhynchus spp. smolts, and (3) only Chum Salmon O. keta smolts utilize both river margin and mid‐channel areas. Some species exhibited distinct peaks and trends in downstream migration timing, including Longnose Suckers Catostomus catostomus, whitefishes (Coregoninae), Arctic Grayling Thymallus arcticus, Lake Chub Couesius plumbeus, Chinook Salmon O. tshawytscha, Coho Salmon O. kisutch, and Chum Salmon. Due to their downstream migration behavior, Pacific salmon smolts out‐migrating in May–July will have the greatest potential for interactions with hydrokinetic devices installed in mid‐channel surface waters of the Yukon and Tanana rivers.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".