Linear Sensor Arrangement for Softwood Grain Angle Measurements by Directional Reflection
Bibliographic record
Abstract
A linear sensor arrangement is presented as a means of measuring the three-dimensional grain angle of wood. The measurement principle is based on an optical characteristic of a wood surface where the microscopic cell structure causes preferential reflection of light perpendicular to the wood grain. This response is notable among the several other techniques for measuring wood grain angle in that it enables identification of diving (out-of-plane) angle in addition to the surface (within-plane) angle. The basic measurement principle has been previously investigated using a circular array of light sensors to measure the spatial distribution of the light reflected from a wood surface. That procedure works reasonably well for surface points near the center of the circle and for modest dive angles. The linear sensor arrangement investigated here is designed to extend measurement functionality so as to be able to measure grain angle at any point along a central line and over a greater range of dive angle. A prototype scanner system is presented together with example experimental results for clear wood samples and for a face knot sample.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".