Early ecosystem establishment using forest floor and peat cover soils in oil sands reclamation
Bibliographic record
Abstract
Early trends of plant community development provide the basis of ecosystem function and reclamation success of oil sand extraction sites. However, few studies have explicitly investigated species-level interactions with different cover soil types, placement depths, and time since reclamation during early plant community development in boreal forests. We investigated effectiveness of forest floor mineral mix (FMM) and peat mineral mix (PMM) cover soils and placement depths (10 and 20 cm) at four research sites 4 to 13 years after reclamation. Outcomes of this study indicate FMM had a more positive influence on woody plant densities, vegetation cover, and species richness than PMM. Species assemblage, composition, dominance, and types (successional stages, habitat types, competitive-stress tolerant-ruderal strategies) also showed FMM cover soil performed better than PMM. Greater vegetation cover and richness on deeper (20 cm) cover soil placements were evident. However, this effect of cover soil depth would likely decrease with time. Dominant and subdominant species on FMM were native and early to late successional, thus trajectory community development on FMM followed typical early succession of boreal forests (from ruderal and annual to perennial communities), while PMM was dominated by non-native and annual forbs which could slow succession and ecosystem recovery.
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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 | 0.001 | 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".