Ecological factors influencing lifetime productivity of pink salmon (<i>Oncorhynchus gorbuscha</i>) in an Alaskan stream
Bibliographic record
Abstract
Ecological factors underlying freshwater productivity and marine survival of pink salmon (Oncorhynchus gorbuscha) were evaluated by analyzing a 30 year time series of local environmental data and censuses of migrating adult and juvenile fish collected at Auke Creek, Alaska. Freshwater productivity was influenced primarily by spawning habitat limitation and less so by stream temperature and flow. Furthermore, a trend of declining freshwater productivity was detected over the time series, which may be related to observed declines in spawning substrate quality and in the duration of the adult migration. Marine survival was highly variable among brood years and was influenced by physical conditions in the nearshore marine environment; warm sea-surface temperatures during nearshore residency were associated with higher marine survival rates, whereas high stream flows late in the fry emigration period were associated with reduced marine survival. Simulations of adult recruitment, based on ecological factors in the freshwater and marine environments, indicated that the productivity of pink salmon in this stream is determined primarily by early marine survival.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Ecological analysis of pink salmon productivity; fisheries science.
The study analyzes ecological determinants of pink salmon productivity.
Ecological analysis of pink salmon productivity; object is fish ecology, not science practice.
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".