Post-hurricane coniferous regeneration in Point Pleasant Park.
Bibliographic record
Abstract
Point Pleasant Park in Halifax, Nova Scotia, sustained catastrophic forest disturbance from Hurricane Juan in September, 2003. This study assessed the adequacy of natural coniferous regeneration in the park in the fall/winter of 2006-2007 and compared the regeneration with pre- and post-disturbance park surveys. The park was stratified using existing trails, transects were spaced 10 m apart, and 20 m2 plots were laid every 10 m. There was a large observed variation of seedling density, with the highest densities being found in the northern and western section of the sample area, and the lowest being found in the south-east. Red spruce was the dominant regenerating species. Balsam fir showed a high variation in density. White pine was less dense and fairly uniformly distributed whereas eastern hemlock had a sparse and patchy distribution. White spruce and exotic species were sparse and tended to be found in areas with lower total regeneration. The comparison with the pre- and post-disturbance park surveys revealed regeneration similar in composition to existing and pre-disturbance forest cover. There are several park management techniques that could benefit park recovery such as the use of donor sites, the importation of favourable conifer species for fill-planting, the culling of some exotic species, and volunteer planting programs.
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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) | 0.001 | 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".