Factors influencing spatial distribution and growth of juvenile lake sturgeon (<i>Acipenser fulvescens</i>)
Bibliographic record
Abstract
Understanding biotic and abiotic factors that influence spatial distribution patterns, condition factor, and growth of lotic fish species within river impoundments is essential for the development of effective management and conservation strategies. This study aimed to compare relative abundance, condition factor, and growth rate of juvenile lake sturgeon (Acipenser fulvescens Rafinesque, 1817) among eight sections of a 41 km long impoundment of the Winnipeg River, Manitoba, Canada. Relative abundance of juvenile lake sturgeon, as measured by catch per unit effort (CPUE), was 3–6 times greater in the two farthest upstream sections when compared with the five farthest downstream sections. Growth in length was slowest for individuals captured in the two farthest upstream sections, moderate in the third section, and highest in the fourth section, with individuals from the fourth section attaining lengths approximately double those from the two farthest upstream sections by age 6. Condition factor varied among sections of the impoundment in a pattern similar to that observed for growth. Given similarities in many environmental factors such as water temperature and water chemistry among sections of this study area, our results provide important insight into how abiotic and biotic factors, combined with behavioural characteristics of this species, may influence distribution patterns and growth of juvenile lake sturgeon within river impoundments.
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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) | 0.001 | 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".