Early regeneration and growth dynamics of <i>Populus tremuloides</i> suckers in relation to fire severity
Bibliographic record
Abstract
Four boreal mixedwood stands burned by the 1999 Black River wildfire in southeastern Manitoba were sampled to determine the effect of fire severity on density and diameter and height growth of trembling aspen (Populus tremuloides Michx.) suckers during the first three postfire years. Analysis of covariance, using prefire aspen basal area as the covariate, indicated that fire severity significantly affected postfire aspen sucker density, with significantly lower density found on severely burned plots. Changes in aspen sucker density over the three postfire years depended on fire severity, with significant changes observed only on scorched and lightly burned plots. Sucker mortality was positively related to the initial sucker density, with more than 80% of the total variance being explained. Fire severity significantly affected the growth of dominant aspen suckers in the first, but not the second and the third, postfire years. The first year of growth initially increased and then remained stable with the increase in density, while the second and third years of growth were not affected by density. Since fire severity within and (or) among burned stands is inherently heterogeneous, the effect of fire severity must be taken into account in predicting postfire density and growth of aspen suckers.
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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 | 0.000 | 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) | 0.000 | 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".