Stand structure differences resulting from post-harvest silviculture in boreal mixedwoods / by Daniel Corbett.
Bibliographic record
Abstract
Under the Ontario Forest Accord, several parcels of land have recently been designated as protected areas reducing the area available for forest management. As a result, forestry companies will likely have to intensify timber production using post harvest silviculture on remaining industrial forestry land to yield the same volumes achieved from fewer operable hectares. I used a chronosequence approach (stands 15-57 yrs) to investigate the question: "Does post-harvest silviculture change forest composition and structural attributes at the stand level?" I sampled overstory, standing dead-wood components, and woody debris of forty-three upland mesic stands in the Gordon Cosens Forest, Kapuskasing, Ontario. Stands were selected to address potential differences in structural attributes resulting from three silvicultural intensities (harvest with no silviculture, harvest with planting and with herbicide tending, and harvest with site preparation, planting, and application of herbicide), across the chronosequence.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".