Oblique radiographic measurement of knot position and orientation in logs
Bibliographic record
Abstract
Abstract A novel X-ray scanner system to identify the positions of knots in logs is described. The scanner has a simple, low-cost design that is suitable for use in medium and smaller sawmills. It makes X-ray measurements in an oblique direction as the log moves longitudinally past the X-ray source and line-detector. This unconventional oblique measurement direction creates a more side-on view that better reveals the spatial arrangement of the knots within the log. This view, when combined with the knowledge that all knots start from along the pith and radiate outwards gives sufficient information to identify knot orientations in space. Experimental oblique X-ray measurements on a sample log are described, followed by the processing and analysis of the measured radiographs, and a comparison of the results with independent measurements of knot locations. With the knot identification algorithms developed, knot axial position could be identified within 11 mm, and knot circumferential orientation with a root mean square (rms) error of 7.9°–11.6° when using a single view X-ray scanner, or 5.6°–7.7° when using a dual view scanner.
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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 | 0.001 | 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) | 0.002 | 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".