Measurement of powder coating coverage on a moving surface
Bibliographic record
Abstract
Various methods exist to measure the areal density of particles resting on stationary surfaces. These techniques can be expensive, intrusive, or time-consuming, and in general cannot be used to measure particulate on a moving surface. We demonstrate an inexpensive oblique light measurement technique using a digital camera to measure the areal density of particles on a moving surface. This measurement technique is applicable for both bright and dark powders deposited on contrasting backgrounds and is insensitive to the precise orientation of particles on the surface. While the areal densities inferred from this technique have a 13–15 % median relative error compared to gravimetric measurements, this error is inflated because the gravimetric measurements themselves have uncertainties between 1 % and 10 %. The technique's utility is demonstrated by measuring the particle deposition on a surface moving at several meters per second, which is an application where other areal density measurements cannot be used.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".