Evaluation of kiln-drying schedules for wild cherry wood (Cerasus avium)
Bibliographic record
Abstract
Wild cherry wood (Cerasus avium) lumber with a nominal thickness of 5 cm from Duzce region in Turkey was dried through conventional kiln drying using two different programs which are unprotective drying schedules, and protective drying schedules. The aim was to obtain the most desirable kiln schedule for keeping the wood quality at an appropriate level up to final moisture content of 12±2% was reached. Intensity of warping (twist, bow, cup, crook) occurrence, superficial, internal and end checks, residual stresses, drying rate, and moisture gradient in the dried woods were measured, and the results were analyzed. The results showed that there was a more homogeneous moisture profile, fewer occurrences of superficial checks, and absence of internal checks in the protective drying schedules due to low warping values compared to the unprotective drying schedules. Therefore, it seems that protective drying schedules might be recommended as optimum program for wild cherry lumber drying at commercial scale from Duzce region.
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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".