Dielectric properties of four softwood species at low-level radio frequencies for optimized heating and drying
Bibliographic record
Abstract
Dielectric heating and drying are important nontraditional technologies for the phytosanitation and quality dehydration of wood products. Unit operation optimization requires, among others, knowledge of the variable dielectric properties of wood so that an optimum dielectric generator matching wood impedance is maintained throughout the process. For this reason, the dielectric properties of four commercially important west coast softwood species were experimentally obtained at various moisture contents, temperatures, and radio frequencies (RF) between 0.1 and 30 MHz. Measurements were carried out on all-sapwood and all-heartwood specimens in both radial and longitudinal directions. Measurements were also done with specimens that were fully saturated with distilled and seawater.All specimens mostly revealed similar qualitative trends in loss factor changes; that is, increases with moisture content and temperature and decreases with increasing frequency. The measurements carried out in the longitudinal direction showed relatively high loss factor values compared to the radial grain direction. Both distilled and seawater saturated loss factors resulted in similar trends and with absolute values hundreds and in some cases thousand times larger than those for specimens in the hygroscopic range.
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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".