Overturning resistance of western redcedar and western hemlock in mixed-species stands in coastal British Columbia
Bibliographic record
Abstract
Specific information about the applied forces that cause trees to fail is required to validate mechanistic models of windthrow in different forest types. Static tree-pulling tests were conducted to examine the overturning resistance of western redcedar ( Thuja plicata Donn ex D. Don) and western hemlock ( Tsuga heterophylla (Raf.) Sarg.) in a mixed species second-growth stand in coastal British Columbia. Although widely used, tree-pulling techniques are not standardized. Data from three inclinometers were used to estimate stem deflection, which was found to increase with tree slenderness. Differing methods of fitting stem curvature had a small effect on estimates of self-loading at failure. The distance of the pivot point from the centre of the stem base increased with tree diameter. Accounting for the correct self-loading at failure produced a small difference in the overall turning moment regressions but did not improve the fit of these regressions. However, this difference increased with tree size and warrants consideration in future tree-pulling tests with large or plate-rooted trees. The stem mass – overturning resistance relationship had the best fit and was not significantly different for these species in spite of their differences in wood density and stem form.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".