Relationship between microgloss uniformity and surface texture of paper
Bibliographic record
Abstract
A customized setup was used to measure the microgloss nonuniformity of paper. This setup can characterize gloss uniformity of an area of one square centimetre at a resolution of 16 x 16 mum2. Beckmann's light scattering model for random rough surfaces was successfully applied to describe the relationship between the surface texture parameters and the microgloss nonuniformity of a large range of coated and uncoated papers. The model, based on the Kirchhoff approximation, suggests that the variation in specular reflectance (gloss) depends only on the RMS roughness, sigma, and on the correlation length, T, of the surface height of the samples. The topography of the paper surfaces was obtained using a WYKO surface profiler. Results indicated that the relationship between the variance of microgloss followed the prediction of the Beckmann's model well. The variance of microgloss was found to be linearly dependent on a dimensionless parameter Ts for most of the samples studied. However, the dependence of the natural logarithm of the average microgloss on the square of rms roughness was nonlinear differing from the model prediction.
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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 | 0.002 |
| 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".