Thermal death kinetics of adult red flour beetle <i>Tribolium castaneum</i> (Herbst) in canola seeds during radio frequency heating
Bibliographic record
Abstract
Thermal mortalities of adult red flour beetles Tribolium castaneum (Herbst) infesting canola seeds at various moisture contents and volumes were determined after radio frequency (RF) heating (i.e. temperature between 30 and 80°C). The mortality of 92% was achieved at the end temperature of 343 K for small-volume (1.96 × 10−4 m3, 0.250 kg) seeds, and the mortality of 99% at 333 K for large-volume (1.77 × 10−3 m3, 2.26 kg) seeds. Regardless of sample volume, the thermal mortalities of the test insects increased significantly after the seed temperature reached 333 K (60°C). The kinetic parameters of the thermal death of the adult T. castaneum were estimated using inverse simulation. The ordinary differential equation-based kinetic model with the Arrhenius temperature-dependent reaction rate constant was solved using the fourth-order Runge–Kutta method. The kinetics followed first-order reaction with the activation energy of 100 kJ/mol. Good agreements were observed between the mortalities predicted using the kinetic model and the experiments (R2 = 0.972–0.987) except for the small-volume seeds at 11% MC (11 g/100 g raw materials) (R2 = 0.741). The predicted lethal times (s) to achieve 95 and 99% mortalities using the kinetic model agreed well with those determined from the experiments.
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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 | 0.000 | 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 | 0.000 |
| 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".