Erosion control blankets, organic amendments and site variability influenced the initial plant community at a limestone quarry in the Canadian Rocky Mountains
Bibliographic record
Abstract
Abstract. Season of seeding and soil amendment with manure mix, wood shavings and erosion control blankets were evaluated over two growing seasons to determine their effect on soil properties and native grass establishment at a Canadian limestone quarry and lime processing plant. A season (fall, spring) of soil amending and seeding did not significantly affect revegetation or soil properties. Site characteristics such as slope, aspect, initial soil nutrients and surrounding plant communities influenced early plant community development and overall effects of soil treatments. Erosion control blankets resulted in the highest seeded plant cover and the lowest non-seeded plant cover despite not significantly changing soil chemical properties. Total nitrogen and carbon significantly increased establishment of seeded grasses and non-seeded species. Increased nitrogen and carbon in the constructed soils were best achieved through addition of manure. Wood shavings did not favour establishment of vegetation and resulted in similar, and in some cases less, vegetation than the controls. Assisted revegetation increased plant cover from < 6 to 50% and reduced cover of non-seeded species. Amendments that modified both chemical and physical soil conditions were best to increase vegetation establishment in the harsh conditions of the quarry.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".