Three-Dimensional Transient Heat, Mass, and Momentum Transfer Model to Predict Conditions of Canola Stored inside Silo Bags under Canadian Prairie Conditions: Part II. Model of Canola Bulk Temperature and Moisture Content
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Bibliographic record
Abstract
<abstract> A three-dimensional transient heat, mass, and momentum transfer model was developed to predict temperatures and moisture contents of canola stored inside silo bags under Canadian Prairie conditions. The developed model calculated the condensation and production of water and heat generated by the respiration of microorganisms inside silo bags. This model was coupled with the soil temperature model developed in part I. These developed models were validated using weather data as input and measured temperatures and moisture contents inside silo bags filled with canola at 9.1%, 10.5%, or 14.4% initial moisture content (MC). The developed models had a poor prediction of the temperature and moisture content of the 14.4% MC canola because the canola seeds spoiled and clumped together in less than four months. The developed models could explain more than 90% of the measured temperatures inside the silo bags filled with 10.5% MC canola without underestimation or overestimation. The average absolute difference was less than 1.9°C ±0.1°C and 0.7°C ±0.0°C inside silo bags with 9.1% and 10.5% initial MC, respectively. The developed models could explain more than 94% of the measured moisture contents of canola stored inside the silo bags with â¤10.5% initial MC. The average absolute difference between measured and predicted moisture contents of canola was â¤0.4% ±0.0% inside the silo bags filled with 9.1% and 10.5% MC canola. Simulation results showed that condensation on the canola seeds mostly occurred at the boundary of silo bags, and canola inside hot spots might produce â¥2.5 fold of heat production, which was measured under small-scale laboratory conditions.
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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 | 0.000 |
| 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) | 0.000 | 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 it