A method for estimating wood chip brightness and its applications<sup>1</sup>This article is a contribution to the series The Role of Sensors in the New Forest Products Industry and Bioeconomy.
Why this work is in the frame
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Bibliographic record
Abstract
Methods for estimating wood chip brightness are important in classifying wood chips in chip piles, stabilizing chip brightness in the pulping process, and reducing bleaching chemical consumption in pulp mills. They also allow us to understand and control factors including outdoor storage in the summer that affect chip and pulp brightness. An accurate off-line method for estimating wood chip brightness has been developed. The method involves a two-stage grinding of air-dried wood chips to powders with small particle sizes and narrow size distributions and measurement of ISO (International Standardization Organization) brightness of the resulting powders. Using this method, ISO brightness values of 20 mill or pilot-plant thermomechanical pulps (TMP) can be linearly correlated, with an r 2 value of 0.885, with ISO brightness of the mill or pilot-plant wood chips. Analyses of wood chips and TMP samples taken from a TMP mill every month for 1 year show that both the chip and TMP brightness values are the lowest in July. The method can be used for laboratory analysis of chip brightness, monitoring of chip brightness monthly variation in pulp mills, and checking the accuracy of the on-line chip brightness measurement system.
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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 | 0.002 | 0.000 |
| 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) | 0.000 | 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 it