Improved life of circular saws used in primary wood processing
Bibliographic record
Abstract
The effects of the Engineered Micro-Geometry (EMG) of the carbide teeth of circular saws on their wear rate and resulting sawing variation for 2-time intervals were studied. The objective was to improve the wear resistance of circular saws used during the primary transformation of wood. The tests were carried out under industrial production conditions with two series of circular saws; 1- with up-sharp tips, and 2- with cutting edges honed to adopt a waterfall geometry. The duration of the tests was 255 min and 645 min. Wood studs were sampled to measure sawing variation. Recession on the rake and clearance faces of the tips as well as the width of the wear land were measured. The wear mechanisms of the cutting edges of both types of saws were studied. Chipping and cracking were the two dominant wear mechanisms observed on the up-sharp tips. Saws with waterfall hone tips showed remarkably reduced chipping and cracking. Wear rate of the latter was notably lower than that of saws with up-sharp tips at both periods of sawing. Between-stud, within-stud, and total sawing variations decreased when saws with modified cutting edges were used.
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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".