Bioprospecting for acidophilic lipid-rich green microalgae isolated from abandoned mine site water bodies
Bibliographic record
Abstract
With fossil fuel sources in limited supply, microalgae show tremendous promise as a carbon neutral source of biofuel. Current microalgae biofuel strategies typically rely on growing high-lipid producing laboratory strains of microalgae in open raceways or closed system photobioreactors. Unfortunately, these microalgae species are found to be sensitive to environmental stresses or competition by regional strains. Contamination by invasive species can diminish productivity of commercial algal processes. A potential improvement to current strategies is to identify high-lipid producing microalgae, which thrive in selected culture conditions that reduce the risk of contamination, such as low pH. Here we report the identification of a novel high-lipid producing microalgae which can tolerate low pH growth conditions. Lig 290 is a Scenedesmus spp. isolated from a low pH waterbody (pH = 4.5) in proximity to an abandoned lignite mine in Northern Ontario, Canada. Compared to a laboratory strain of Scendesmus dimorphus, Lig 290 demonstrated robust growth rates, a strong growth profile, and high lipid production. As a consequence, Lig 290 may have potential application as a robust microalgal species for use in biofuel production.
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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) | 0.000 | 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".