Shigometer and electrical resistance studies of paper birch / by Robert Bowen
Bibliographic record
Abstract
The Shigometer was evaluated as an instrument for detecting \nred heart of paper birch. The Shigometer accurately detected the \npresence of red heart at a 50% decrease from the maximum reading \nrule but sometimes failed to precisely define its outer limits. \nAlthough it did not always correctly detect the presence or precise \nlocation of discoloured wood, it was able to correctly detect the \npresence of discoloured wood within a few centimetres in \napproximately 85% of attempts. There was a general increase in ion \nconcentrations in the red heart as compared to the clear wood. The \nions appear to accumulate in vessels along the clear wood to \ndiscoloured wood transition zone, in the ray parenchyma in the \ntransition zone and in the discoloured wood. Following wounding \nthere was an increase in soluble and insoluble potassium. The \nShigometer readings were found to be correlated with mobile ion \nconcentrations of potassium and magnesium. Because few \nmicroorganisms were found in association with the red heart, it is \nfelt that the initial accumulation of ions may be a wound response by \nthe tree.
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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) | 0.005 | 0.001 |
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".