The impacts of hydrology on the life cycle of California white sturgeon
Bibliographic record
Abstract
Anthropogenic alterations, such as water diversions for human consumption, have degraded habitat quality for aquatic ecosystems worldwide. One of these heavily modified habitats is the San Francisco Estuary, home to a distinct population of white sturgeon ( Acipenser transmontanus). This population has been in decline, driven by intermittent recruitment and mortality by factors such as overharvesting and harmful algal blooms, and is being considered for listing under the California Endangered Species Act. Little is known about the early stages of white sturgeon life cycle and how hydrological alterations affect them. In this paper, we use general linear mixed models to identify relations between the hydrology in the San Francisco Estuary and aspects of the white sturgeon life cycle that affect white sturgeon early stages. We find that the visitation of spawning sites and the probability of catching young-of-year white sturgeons are significantly correlated with increased Delta outflow, i.e., an increase in water flowing out of the Estuary. This information will be critical to inform management strategies that promote the persistence of white sturgeon in California.
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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 | 0.001 | 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) | 0.001 | 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".