Thermal Imaging to Identify Western Canadian Wheat Classes
Bibliographic record
Abstract
Varietal purity is one of the important factors in grain grading. In the laboratory, wheatclasses and varieties are determined by trained professionals. For online classification of wheatclasses and varieties, several approaches have been made with image processing technology, butthe classification efficiency was poor and inconsistent. The capability of thermal imaging system forthe identification of wheat classes was investigated. In this study, eight classes of western Canadianwheat were subjected to heating and cooling treatments. During treatment, the sample was heatedor cooled one kernel at a time and then surface temperatures were imaged with the thermal camera.In both treatments, the temperature profiles were dissimilar for all classes. The rate of heating andcooling of the germ end was slower than that of other parts of the kernel for all classes. The averagetemperature of the kernel was in the range of 37.1 (CPSW) to 45.6oC (CWRS) during heating and18.9 (CWRW) to 22.3oC (CWAD) during cooling treatments. The temperature difference betweenkernel average and germ average was 1.7 to 4.1oC in heating and 0.8 to 1.6oC in cooling treatments.The performance of this system must be studied for bulk grain to evaluate the suitability for onlineapplication in grain handling facilities.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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; both teacher heads agree on what is shown here.
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".