Effects of radial force and log position on the stem on ring-debarker efficiency in frozen black spruce logs
Bibliographic record
Abstract
The effect of the radial force applied by a ring debarker tip to frozen black spruce logs, obtained at three positions on the stem, was studied. A one-arm ring-debarker prototype was developed, which controlled the radial force, rake angle, and cutting and feed speeds. The experiment consisted of debarking logs using three different levels of radial force. The rake angle (80°), tip overlap (20%), and cutting and feed speeds were kept constant. Debarking quality was evaluated by two criteria: the proportion of bark remaining on log surfaces and the amount of wood in bark residues. Log characteristics (dimensions, eccentricity, and knot features), bark/wood shear strength, and basic densities of sapwood and bark were also measured. Experiments revealed that log position on the stem did not affect debarking quality. The results also showed a significant effect of the radial force: the amount of bark remaining on log surfaces increased and the proportion of wood in bark residues decreased as radial force decreased. The effects of log eccentricity, bark/wood shear strength, and the proportion of knot surface on the debarking quality were examined. These results give useful information to improve debarking quality within the studied range of radial force, log diameter, and debarking parameters.
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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 | 0.001 |
| 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".