Robust, high-productivity phototrophic carbon capture at high pH and alkalinity using natural microbial communities
Bibliographic record
Abstract
Bioenergy with carbon capture and storage (BECCS) has come to be seen as one of the most viable technologies to provide the negative carbon dioxide emissions needed to constrain global temperatures. In practice, algal biotechnology is the only form of BECCS that could be realized at scale without compromising food production. Current axenic algae cultivation systems lack robustness, are expensive and generally have marginal energy returns. Here it is shown that microbial communities sampled from alkaline soda lakes, grown as biofilms at high pH (up to 10) and high alkalinity (up to 0.5 kmol m−3 NaHCO3 and NaCO3) display excellent (>1.0 kg m−3 day−1) and robust (>80 days) biomass productivity, at low projected overall costs. The most productive biofilms contained >100 different species and were dominated by a cyanobacterium closely related to Phormidium kuetzingianum (>60%). Frequent harvesting and red light were the key factors that governed the assembly of a stable and productive microbial community.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".