Assessing the relative culpability of <i>Simulium</i> (Diptera: Simuliidae) species in recent black fly outbreaks along the middle Orange River, South Africa
Bibliographic record
Abstract
Black fly along the Orange River are major pests of livestock and labour-intensive agriculture, causing annual estimated industry losses in excess of US$30 million. The problem is attributed to winter high flows, with the main pest species being Simulium chutteri Lewis, 1965, although Simulium damnosum Theobald, 1903 and Simulium impukane de Meillon, 1936 may also be periodically problematic. During 2011, black fly outbreaks along the middle Orange River were perceived by farmers to have worsened and attributed to S. impukane. Here, we investigate the likelihood of this being the case, using a weight-of-evidence approach incorporating ecohydrological data. Results showed that it is unlikely that the 2011 outbreaks were caused by S. impukane, and more likely that the main outbreak cause remains S. chutteri. Sustained high flows and turbidity levels favour S. chutteri species over the other species of black fly, while flow conditions for a species such as S. impukane were favourable for 1% of the time only. However, during periods of lower flow and lower turbidity, other species of black fly may be favoured and contribute towards periodic outbreaks. We conclude that black fly control should focus on management issues around the control programme.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".