Effectiveness of five soil reclamation and reforestation techniques on oil and gas well sites in northeastern British Columbia
Bibliographic record
Abstract
McConkey, T., Bulmer, C. and Sanborn, P. 2012. Effectiveness of five soil reclamation and reforestation techniques on oil and gas well sites in northeastern British Columbia. Can. J. Soil Sci. 92: 165-177. Techniques developed for forestry landing reclamation were applied to five oil and gas well sites in northeastern British Columbia to ameliorate soil and facilitate reforestation. Treatments implemented in fall 2003 and spring 2004 were tillage, wood chip mulch, tillage+wood chip mulch, tillage+incorporated wood chips, brush mats and a control. Lodgepole pine (Pinus contorta var. latifolia) and white spruce (Picea glauca) seedlings were planted. Soil and vegetation were assessed (bulk density, soil mechanical resistance, water content, air filled porosity, water retention, least limiting water range, nutrient availability, seedling survival and growth) throughout 2004 and 2005 growing seasons. Tillage improved soil physical condition, reducing soil mechanical resistance and bulk density; treatments did not affect soil chemical properties. Treatments did not significantly affect species survival; after 6 yr, spruce height and root collar diameter improved with tillage but treatments did not affect pine. Brush mats led to increased spruce growth. Regression relationships between tree performance and soil condition were significant, but generally did not explain large variability. More elaborate soil physical condition measures were no better than bulk density for predicting seedling performance, but relative bulk density and least limiting water range may be useful for evaluating soil productivity.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".