Thinning to meet sawlog objectives at shorter rotation in lodgepole pine stands
Bibliographic record
Abstract
We modelled how pre-commercial and commercial thinning affects development of merchantable timber, specifically large sawlogs (>20 cm diameter), on various site qualities and at different harvest ages. Data from juvenile permanent sample plots from post-harvest regenerated lodgepole pine stands in Alberta were projected using the Mixedwood Growth Model (MGM 21). Pre-commercial thinning (PCT) and different levels of commercial thinning (CT) with PCT were assessed on stands of good, medium, and fair site quality. Results show site quality alone had the greatest impact on merchantable yields with good sites producing ∼1.5 times the yield of medium and ∼4.3 times that of the fair sites. Moderate thinning on good sites produced a greater quantity of large sawlogs (>20 cm diameter) and their associated volume over unthinned stands than that on medium or fair sites, though thinning positively influenced total yield on these sites as well. On good sites, at age 50, CT treatments produced about ∼50 m3/ha more volume of large sawlogs (>20 cm) than the control; such gain drops to 18 m3/ha on medium sites. In addition, the mean annual increment culminated earlier on good sites, also enabling earlier harvest.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".