Effects of wood species on the energy requirements and size distribution of strands produced by a strander-canter
Bibliographic record
Abstract
The effects of wood species on the performance of the strander-canting process were studied. Logs of balsam fir (Abies balsamea (L.) Mill.), black spruce (Picea mariana (Mill.) B.S.P.), and jack pine (Pinus banksiana Lamb) were processed under two temperature conditions (-13.3 °C and 22.3 °C). The cutting and feed speeds, rake angle, cutting width, and strand thickness were kept constant. The strander-canting process was evaluated by the strand dimensions and yield, as well as by the energy requirements. The results showed that wood species significantly affected the proportions of strands and fines, maximum power, mean energy consumption, and specific cutting energy when processing the logs under frozen conditions. In unfrozen conditions, wood species only affected the strand width and the maximum power. Unfrozen logs produced higher proportions of strands and a lower volume of pin chips and fines than frozen logs. The maximum power, mean energy consumption, and specific cutting energy were, on average, 2 to 4 times higher for the processing frozen logs than for unfrozen logs.
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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".