Approaches to the evaluation and management of the fish stock in Kainji Lake, Nigeria
Bibliographic record
Abstract
Estimates of potential yield for Kainji Lake, and the methods of analysis by earlier workers are discussed. Also summarized is the state of the fishery after impoundment, between 1969 and 1971, based on experimental gillnet catches. Recent sampling of the young of the year along the littoral margin indicates that most of the commercially important species have spawned successful1y in the lake. An intense fishing mortality of juvenile fish, owing tothe use of small mesh nets by local fishermen, presents a possible threat to the future establishment of the fish in the lake. The results of gill-net selection studiesbased on HOLT'S (1957) method are given.The data have been extracted from experimental gill-net catches with graded fleets of nets between 1969 and 1971. Recommendations based on the above studies have beenmade to ensure a successful establishment of the fish species in the lake and an increase in catch-per~unit effort in subsequent years.
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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 | 0.007 |
| Science and technology studies | 0.001 | 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 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".