Energy dynamics and growth of Chinook salmon (Oncorhynchus tshawytscha) from the Central Valley of California during the estuarine phase and first ocean year
Bibliographic record
Abstract
The greatest rates of energy accumulation and growth in subyearling Chinook salmon ( Oncorhynchus tshawytscha ) occurred during the first month following ocean entry, supporting the importance of this critical period. Data from an 11-year study in the coastal ocean off California and the San Francisco Estuary revealed that juvenile salmon gained 3.2 kJ·day–1and 0.8 g·day–1, representing 4.3%·day–1and 5.2% day–1, respectively, relative to estuary exit values. Little gain in energy (0.28 kJ·day–1) or size (0.07 g·day–1) occurred in the estuary, indicating that the nursery function typically ascribed to estuaries can be deferred to initial ocean residence. Calculated northern anchovies ( Engraulis mordax ) equivalents to meet energy gains were one anchovy per day in the estuary (8% body weight·day–1) and about three per day immediately following ocean entry (15% body weight·day–1). Energy content in the estuary was positively related to higher salinity and lower freshwater outflow, whereas in the ocean, cooler temperatures, lower sea level, and greater upwelling resulted in greater gains. These results suggest that greater freshwater flows, warmer sea temperatures, and reduced or delayed upwelling, all of which are indicated by some (but not all) climate models, will likely decrease growth of juvenile Chinook salmon, leading to reduced survival.
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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 | 0.000 |
| 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".