Trends in an emerging artisanal fishery of the African cyprinid <i>Rastrineobola argentea</i> in Lake Nabugabo, Uganda
Bibliographic record
Abstract
Abstract Fishing pressure can have strong impacts on fish populations, driving declines in abundance and, occasionally, changing life history traits. However, much of our current understanding of these phenomena derives from studies conducted decades or even centuries after the onset of fishing. Newly established fisheries provide an excellent opportunity to understand this critical early phase. Temporal trends in catch data and life history traits of the cyprinid fish Rastrineobola argentea (Pellegrin), now the target of a burgeoning artisanal fishery in Lake Nabugabo, Uganda, were analysed. Results showed that the R . argentea fishery intensified and became more selective during the first decade since its establishment (2008–2019), while catch‐per‐unit‐effort of R . argentea (fisheries‐independent abundance) at repeatedly sampled sites in the lake decreased over this same time period. Size‐adjusted egg volume and ovary mass increased significantly over the time period, which may reflect a density‐dependent response to a fisheries‐induced population decline.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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) | 0.004 | 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 teacher head, 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".