Laboratory-based nitrogen mineralization and biogeochemistry of two soils used in oil sands reclamation
Bibliographic record
Abstract
MacKenzie, M. D. and Quideau, S. A. 2012. Laboratory-based nitrogen mineralization and biogeochemistry of two soils used in oil sands reclamation. Can. J. Soil Sci. 92: 131-142. In the Athabasca oil sands region of Alberta, Canada, peat mineral and upland forest floor mineral soils are salvaged and stockpiled for reclamation. Previous work showed that sites reclaimed with forest floor mineral soil had better understory regeneration and nitrogen dynamics more similar to naturally disturbed ecosystems. Both soils and a mixture of the two were compared in laboratory incubations by examining nitrogen mineralization (over 45 wk) and factorial fertility additions (4 wk trial with NPK) on microbial community structure and nutrient availability. Nitrogen mineralization indicated forest floor mineral soil had lower release rates and a higher estimated labile nitrogen pool than peat mineral soil. Nitrogen mineralization in mixed soil started like peat mineral soil and finished like forest floor mineral soil. Fertility additions influenced microbial community structure less than soil type. Multi-response permutation procedure indicated the forest floor mineral soil microbial community was significantly different from peat mineral and mixed soil communities. Control nutrient profiles differed from those with added NPK. Forest floor mineral soil retained nitrogen as ammonium, while peat mineral and mixed soils were nitrate dominated. Reclamation will require all soil types to be used and these data will help determine soil placement prescriptions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".