Bibliographic record
Abstract
Red maple ( Acer rubrum L.) is becoming increasingly dominant in forest stands throughout the eastern United States. To investigate the reasons for the increase, we examined the development of red maple and oak ( Quercus spp.) seedlings and stump sprouts following the harvest of oak-dominated stands. Within 7 years after harvest, red maple seedlings were present in far greater numbers and captured more growing space than all oaks combined. Growing space occupied by red maple stump sprouts exceeded oak sprouts by a ratio of 3.5:1. Through stump sprouts alone, red maple fully recaptured the amount of growing space it had previously occupied in the overstory 7 years after harvest. Results from similar but older stands show that red maple dominance is sustained into the third decade of stand development. Red maple surpassed all oaks combined in rapid site capture through both seed-origin and sprout-origin regeneration. Red maple’s superior ability to regenerate by sprouts is particularly favored by timber harvesting following a history of management and disturbance regimes that permit the accumulation of suppressed small-diameter red maple stems. Among the events and processes that promote stand conversion, timber harvesting may be the major proximal cause of the widespread, increasing dominance of red maple.
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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".