Diversity of Waterbirds in Chobe River, Botswana
Bibliographic record
Abstract
The Chobe Riverfront has a higher diversity of large mammalian species. This study investigated the seasonal variation in the waterbirds diversity along the Chobe River, Botswana, from 2019 to 2025. Eight ground count surveys conducted from a vehicle were done during the wet and dry seasons across these years. Observers used binoculars and the naked eyes to count birds in the mornings. The Shannon-Wiener Diversity index was used to compute the seasonal species diversity, with ANOVA applied to test for significant differences of the diversity indices between years and seasons. The analyses suggested that the Chobe River has a higher diversity of waterbirds, but with no significant differences in diversity between the wet and dry seasons and years. Results showed that more family groups were recorded in the wet season, with ducks, geese, storks, pochards, cormorants, darters, herons, egrets, and bitterns being most abundant. In the dry season, the most abundant species included herons, egrets, bitterns, lapwings, jacanas, storks, ducks, and geese. This study demonstrates the importance of the Chobe River as an important bird area and its management is significant for the conservation of many avian species in the region.
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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 | 0.001 |
| 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".