Bur oak (<i>Quercus macrocarpa</i>) biomass production on a former coal mine site: positive effects of coppicing on rapid recovery of growth and yield
Bibliographic record
Abstract
Ten-year-old bur oak (Quercus macrocarpa Michx.) saplings established on the exposed, infertile, treeless barrens of a former coal mine site in New Brunswick, Canada, were harvested to assess the effects of subsequent coppicing on regrowth parameters and biomass production. Two years after harvesting, coppice height growth exceeded that of the original 10-year-old saplings by 20%. Mean stem numbers were 1.2 and 6.7 for 10-year-old and coppiced trees, respectively. Mean dry mass recovered after 2 years with 214, 112, and 207 g for 10-year-old saplings and the 1- and 2-year-old coppices, respectively. Site quality of the broken shale rock overburden was similar across four of the five sites, with the exception that one site had twice the soil nitrogen (N) at 0.123% than the other four site types, which had an average of 0.064% N. This high N site had 2.3-fold the productivity of the mean for the other four sites. Mean coppice stem height showed the strongest predictive relationship to total coppice dry mass when compared with the greatest stem height, greatest or mean stem basal diameter, or coppice stem number. The most dramatic result of this bur oak coppicing experiment was the rapid recovery of height growth, biomass production, and observable stem quality within coppices over the 2-year period following harvesting of the original, 10-year-old saplings.
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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".