Responses of Red‐Osier Dogwood to Oil Sands Tailings Treated with Gypsum or Alum
Bibliographic record
Abstract
The application of composite or consolidated tailings (CT) technology provides Alberta's oil sands industry with a means of reducing the volume of the fines fraction in extraction tailings and allows for faster reclamation and revegetation of mining sites. This study examined the effects of coagulant aids (gypsum and alum), used in the production of CT, on the ion content, growth, and survival of greenhouse-grown red-osier dogwood (Cornus sericea L. subsp. sericea). Seedlings were planted in gypsum-CT and alum-CT substrates, and compared with those planted in reclamation material (salvaged peat and till). The seedlings were bottom-watered with one of the following: (i) Hoagland mineral solution prepared in deionized water (Epstein, 1972); (ii) Hoagland solution in gypsum-based CT release water; or (iii) Hoagland solution in alum-based CT release water. Pore water of CT substrates and CT release waters had similar chemical characteristics, including salinity levels. However, plants in CT substrates had higher concentrations of ions (particularly Na and B), reduced growth, and higher mortality than plants in reclamation material and treated with CT waters. The presence of H2S indicated low-oxygen conditions in the CT substrates, while in the reclamation materials with CT release water treatments, no evidence of sulfides was observed. Low-oxygen conditions in the CT substrate treatments may have interfered with plant exclusion mechanisms for Na and B. Therefore, substrate properties may modify responses of reclamation plants to pore water chemistry due to the effects on oxygen availability to roots.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".