In Vitro Selection of Boreal Ectomycorrhizal Fungi for Use in Reclamation of Saline‐Alkaline Habitats
Bibliographic record
Abstract
Abstract To identify appropriate species of ectomycorrhizal fungi for use in the reclamation of saline‐alkaline sites, such as the composite tailings (alkaline, with high sodium, sulfate, and calcium) produced by the Canadian tar sands industry, pure cultures of nine fungal species indigenous to the Canadian boreal forest were grown on media containing different levels of CaCl2, CaSO4, NaCl, or Na2SO4, as well as on medium containing composite tailings (CT) release water, and on media at four different pH levels. Members of the Boletales (Suillus brevipes, Rhizopogon rubescens, and Paxillus involutus) and Amphinema byssoides (Aphyllophorales) were sensitive to alkalinity, and their growth was completely inhibited by CT release water. Laccaria and Hebeloma spp. (Agaricales) as well as Wilcoxina mikolae (Pezizales) were tolerant to alkalinity and survived on the medium containing CT release water. Calcium chloride proved to be the most toxic of the salts tested. Growth of seven isolates of Laccaria bicolor and three isolates of Hebeloma crustuliniforme on media containing CaCl2 and release water showed low intraspecific variation. A combination of fungal species, each with its own beneficial characteristics, is recommended for the inoculation of seedlings to be outplanted onto composite tailings.
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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 | 0.000 |
| 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".