A Statistical Approach for Determining the Impact of Sensor Orientation and Electrode Type on Moisture Content Measurements in Eastern White Pine
Bibliographic record
Abstract
Current methods for quantifying the moisture content (MC) of wood species involve the measurement of electrical resistance between two installed electrodes and the use of existing empirical correlations to evaluate the MC. The objective of this study was to statistically examine the impact of sensor orientation and electrode geometry on MC measurements in 126 eastern white pine samples with electrodes placed along the grain of the wood (longitudinal) and across the grain of the wood (tangential) using six different fasteners. MC measurements were taken and electrical resistances were measured in both directions at temperatures ranging from -10℃ to 40℃ as samples reached steady state at different relative humidity levels. It was statistically determined that grain orientation does not need to be considered (p>0.05) when assessing MC in eastern white pine, while electrode type should be considered (p<0.05) when fasteners of high vs. low contact surface areas are compared.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".