In vitro selection of ecologically adapted ectomycorrhizal fungi through production of fungal biomass and metabolites for use in reclamation of biotite mine tailings
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Mineral weathering plays an important role in poor-nutrient environments such as mine spoils and tailings. Ectomycorrhizal (ECM) fungi are able to enhance mineral weathering through different mechanisms, thereby increasing the availability of minerals and nutrients to plants. Six ECM fungi (Cadophora finlandia, Cenococcum geophilum, Hebeloma crustuliniforme, Lactarius aurantiosordidus, Paxillus involutes, and Tricholoma scalpturatum) were tested here for their tolerance to biotite-quartz-rich mine tailings. Either solid- or liquid-medium methods were used for in vitro selection of ECM fungi for their ability to grow on mine tailings. ECM fungi were selected based on their mycelial radial growth and metabolite production (ergosterol and low-molecular-mass organic acids, LMMOAs). We found a strong correlation between fungal ergosterol content and mycelial radial growth using the solid-medium method. However, the liquid-medium method was more appropriate for ergosterol synthesis and permitted direct measurement of organic acid production. We found that LMMOAs were exuded by ECM fungi, which solubilized mine tailings for their own growth and nutrition. Finally, we concluded that the ECM fungi C. finlandia and T. scalpturatum are the species most tolerant to tailings and could potentially improve the survival rate, growth, and health of white spruce seedlings planted on biotite mine spoils and tailings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it