Climate-sensitive height–age models for top height trees in natural and reclaimed oil sands stands in Alberta, Canada
Bibliographic record
Abstract
Climate-sensitive height–age models were developed for top height trees of trembling aspen (Populus tremuloides Michx.), jack pine (Pinus banksiana Lamb.), and white spruce (Picea glauca (Moench) Voss) in natural and reclaimed oil sands stands. We used stem analysis data collected from the Athabasca oil sands region in northern Alberta, Canada, and climate data generated by the ClimateWNA model. Height–age trajectories differed between top height trees in natural and reclaimed stands for jack pine and white spruce, but not for trembling aspen. At a given age, white spruce top height trees were taller and jack pine top height trees were shorter in reclaimed stands than those in natural stands, suggesting that it is easier to achieve similar forest productivity for oil sands sites reclaimed with white spruce stands than for sites reclaimed with jack pine stands. The principal climate variables were growing season (May to September) precipitation averaged over the previous 10 years for trembling aspen and jack pine and summer (June to August) precipitation averaged over the previous 10 years for white spruce. These variables had positive effects on the height–age trajectories.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".