A New Field Procedure and Method of Analysis to Evaluate the Performance of Bacillus thuringiensis subsp. israelensis Liquid Formulations in Streams and Rivers
Bibliographic record
Abstract
Many field tests have shown Bacillus thuringiensis subsp. israelensis ( Bti ) to be an effective simuliid larvicide. However, literature indicates that an effective evaluation and comparison of Bti -based formulations when tested in streams or rivers is difficult. Most field trials have been conducted in different rivers (different discharge, river profile, water temperature, suspended matter, larval species, etc.), thus rendering the evaluation of the performance of liquid formulations of Bti very arbitrary or even impossible. A new field procedure is proposed to evaluate the performance of liquid formulations of Bti in the same lotic environment and under similar abiotic and biotic conditions. The procedure, based on a system of gutters located on the bank of a stream, showed very good reproducibility of the mortality levels of the target pest(s) recorded at various distances (stations) along the stream over a two-year field trial, proving the efficacy of the system. The system allows either a single formulation or different formulations to be tested repeatedly in the same portion of a stream, thereby providing a more accurate evaluation of the performance of a Bti formulation or a much better comparison between different formulations. The use of the probit model (allowing comparison of slopes and intercepts) gives a reliable statistical value for the analysis of the results. Moreover, this system is not expensive and can be transferred easily to other streams or rivers.
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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 | 0.001 |
| 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) | 0.000 | 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".