Temperature drop sensor for monitoring kiln drying of lumber
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The main objective of this study was to test a new sensor based on the temperature drop across the load (TDAL). The TDAL sensor was designed to determine the transition point between wet and dry wood without any specific information about the drying process. When additional information is available, the TDAL sensor can also be used to monitor drying rate and estimate the drying end-point. In this study, three potential applications of TDAL sensor for lumber drying were explored, namely, to monitor drying rate, to detect the transition point between wet and dry wood, and for determination of drying end-point after calibration. For the first application, it was demonstrated that the transition point between wet and dry wood coincides with the time at which the TDAL decreases with time at a constant logarithmic slope. For the second application, the TDAL sensor was calibrated with nine experimental drying runs, and the end-points determined with the calibrated TDAL sensor did not show a significant difference with the end-points determined by the in-kiln MC meter. Finally, the TDAL sensor was used to monitor drying rate during drying.
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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