Fisheries studies on Lake George and Kazinga Channel: first quarter final report June/July 2001
Bibliographic record
Abstract
FIRRI surveyed the fisheries of Lake George and Kazinga Channel between 20th June and 20th July 2001. This was the second survey FIRRI has conducted for the ILMproject on the water system. The first survey was conducted during November 2000.These data, the analyses and accompanying reports contribute to baseline information for the fishery being collected with the support of ILM that is required for lakewide planning and management. Eight fish landing sites (6 on Lake George) namely; Kahendero, Hamukungu, Kasenyi, Kashaka, Mahyoro, Kayinja (2 on Kazinga Channel) namely; Katunguru -K and B fall within the focus of ILM and were surveyed during November 2000 and June/July 2001over a three day period at each landing site in 2001 (Mahyoro 2 days). In November 2000, each landing was sampled once. FIRRI conducted a rapid FS and concurrently aCAS. All results are reported by landing site and then summed up (Global) for 8 sites on Lake George and Kazinga Channel.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".