Floristic dynamics of Appalachian pine-oak forests over a prescribed fire chronosequence
Bibliographic record
Abstract
Vegetation dynamics after prescribed fire were modeled on three mountains in the George Washington National Forest representing a chronosequence of conditions since burning: pre-burn, and 1, 2 and 12 years post-treatment. Vegetation structure was more affected by environmental and spatial (burn intensity) gradients than by time since burning. Significant fire effects occurred on southwest aspects and upper slopes, especially among the sapling and shrub strata. Pine and oak regeneration abundance was not affected by fire but shade tolerant tree seedlings decreased, and shade intolerant seedlings increased in importance as a result. Percent cover and richness of herbaceous species increased, partly due to the post-fire germination and growth of various forbs and graminoids. Fire did not affect the abundance of exotic invasive species, but its effects on Ailanthus altissima were inconclusive. Low overstory mortality and prolific sprouting of ericaceous shrubs suggests that understory vegetation effects from single burns are temporary.
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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) | 0.001 | 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".