Longer-Term Volume Trade-offs in Spruce and Jack Pine Plantations Following Various Conifer Release Treatments
Bibliographic record
Abstract
We assessed growth responses 10 years post treatment for 31 combinations of site, species, and treatments from six studies in Ontario, Canada, to determine if conifer release treatments increase gross total conifer volumes but decrease gross total stand volumes in boreal forests. Treatments included single and multiple herbicide application or motor-manual and mechanical conifer release. Treatment effects on 10th-year gross total preferred conifer and total stand volumes ranged from −49% to +556% and −71% to +116%, respectively, compared to the untreated controls. We projected net merchantable stand volumes (NMV) from 10 years post treatment to 60 years of age. These projections indicate that NMV of preferred conifers at age 60 could range from 7.4 m3 ha−1 to 232.4 m3 ha−1. The variation in observed and predicted volumes can be attributed to site characteristics, tree species, ecology, and treatment efficiency.
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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 | 0.000 | 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) | 0.001 | 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".