The decline of the native fisheries of Lakes Kyoga and Victoria and the impact of Nile perch, Lates niloticus on these fisheries
Bibliographic record
Abstract
There has been a decline almost to the total disappearance and in some cases apparently the extinction of most of the native fish species of Lakes Victoria and Kyoga since the development of the fisheries of these lakes begun at the beginning of this century. The Nile perch, Lates niloticus, a large voracious predator which was introduced into these lakes about the middle of the century along with several tilapiine species is thought to have depleted stocks of other fish. But other factors, such as overfishing, changes in the habitat which can result in fish kills or affect breeding and recruitment, plus competition with other species, appear to have contributed to the diminution in the stocks of other fish.The available information indicates that by the time the Nile perch was established, the stocks of the native tilapiine species had been reduced by over fishing. The Labeo victorianus fishery had similarly been destroyed by intensive gill netting of gravid individuals on breeding migrations. L. niloticus is however, capable of depleting the stocks of species which have disappeared and could have consumed the remnants - thus preventing their recovery. It is also directly responsible for the decline in the populations of the haplochromine cichlids which were abundant over most of these lakes when it was established. The native tilapiine species were also affected by the introduced species which have similar ecologicalrequirements.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".