Time‐dose‐mortality modelling and virulence indices for six strains of <i>Verticillium lecanii</i> against sweetpotato whitefly, <i>Bemisia tabaci</i> (Gennadius)
Bibliographic record
Abstract
Abstract: Bioassays of six strains of Verticillium lecanii (Zimmermann) Viégas were conducted with the sweet potato whitefly, Bemisia tabaci . For inoculation, batches of third‐instar whitefly nymphs on sweetpotato seedlings were immersed in conidial suspensions of five dosages at concentrations from 10 3 to 10 7 conidia/ml. Each dosage was used to inoculate 150–250 nymphs. The nymphs were maintained at 25°C, under 95% RH, photo phase of 16 : 8 (L : D) and observed daily for mortality. The resulting data were analysed over 8 days by a complementary log‐log (CLL) time‐dose‐mortality model, based on the Hosmer–Lemeshow test, analysing the time‐dose trends for five concentrations of six strains of V. lecanii simultaneously. The parameters from the model were used to estimate the virulence indices (the values of LC 50 ) of six strains against B. tabaci . Based on the time‐dose‐mortality relationships fitted and the virulence indices, the virulence of the six strains of V. lecanii for B. tabai was compared. Results indicated that the strain Vl6063 imported from Canada and the domestic strains V3450 and Vp28 derived from B. tabaci and a scale insect, respectively, were more virulent than the others with LC 50 values of 2.57 × 10 5 , 6.03 × 10 5 and 6.03 × 10 5 , respectively.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".