THE RELATIVE MERITS OF NATIVE TRANSPLANT PLUGS AND TOPSOIL ISLANDS IN THE ENHANCEMENT OF UNDERSTORY BIODIVERSITY ON RECLAIMED MINELANDS
Bibliographic record
Abstract
In northeastern Ontario, Canada, mine tailings and lands rendered barren by smelter emissions are commonly revegetated using a grass-legume mixture, then planted with native trees, mostly conifers such as Red, White and Jack Pine. Vigorous colonization by native pioneer tree species such as White Birch and Trembling Aspen occurs, as well as that of native herbs associated with forest openings, such as Asters and Goldenrods. However, it is rare for the herbs and shrubs found in the understory of a mature pine forest to colonize these artificially wooded sites. Native understory species have been transplanted from natural habitat at an experimental level over a number of years on grassed smelter-affected barrens and grassed tailings, to determine whether such transplants survive and spread. Small islands of forest topsoil have also been established on grassed tailings. The source of native plugs has been predominantly mature Jack, Red and White Pine forest, but species adapted to naturally exposed sites such as sand dunes have also been transplanted with success. Not surprisingly, the species that spread most readily are those possessing rhizomes or stolons, such as Canada Mayflower (Maianthemum canadense) and Starry False Solomon's Seal (Smilacina stellata) in the case of plugs, and Spreading Dogbane (Apocynum androsaemifolium) in the case of topsoil islands. Since results so far suggest that both approaches are valid, the relative advantages of each are critically appraised.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".