Effects of Knife Jointing and Wear on the Planed Surface Quality of Northern Red Oak Wood
Bibliographic record
Abstract
Jointing is a technique to obtain the same cutting circle for all knives mounted in a cutterhead of a peripheral knife planer.Initially the jointed land at thc cutting edge has a 0 degree clearance angle that becomes negative with workpiecc motion relative to the cutterhead and as the cutting edge wears.Jointed knives may crush cells on the planed surface and affect the quality and performance of wood for end ~lscs.Wc evaluated the gluing properties of northern red oak planed surlhceh that had been planed using one of three jointed land widths, over four levels of knife wear.Under these cutting conditions.surface roughness significantly influenced gluability more than cellular damage.In sum, gluing performance was positively affected by knife wear, and no variation in gluing performance iumong the jointcd land widths studied existed.In samples after accelerated aging, the effects of wear on gluing were more pronounced, with an improvement in gluing performance, associated with an increaw in surface roughness and permeability with increased knife wear.These results suggest a jointed land of 1.2 tnm as the maximum allowable width for planing red oak wood prior to gluing.Also.thc planed surfacc gluability of this wood may be enhanced using a knife with the rake face recession of 132 pm and the clearance face recession of 438 pm, which results in a surface roughness ol' 10 prn R ,,,,,,.Kr\.n,o~.rl\:Planing.knife iointing.wear.gluing properties, northern red oakJointing is a common practice applied to peripheral knife planers to produce an equal cutting circle for all knives mounted in a cutterhead.An abrasive stone is passed over the knife edges as the cutterhead turns at its normal cutting speed.Any projecting knife edge is ground back.ensuring that all the edges lie in a common cutting circle.Thus, each knife can work in a uniform manner taking chips of equal thickness (Dunsmore 1965;Hoadley 2000).Jointing makes knife edges more wearresistant, and it is sometimes wrongly repeated as a sharpening process.' Mcmbcr o l SWST.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.004 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".