Algal growth enhancement by bacteria: Is consumption of photosynthetic oxygen involved?
Bibliographic record
Abstract
Pseudomonas diminuta and P. vesicularis, two obligate aerobes isolated from laboratory algal cultures, stimulated the growth of the green microalgae Scenedesmus bicellularis and Chlorella sp., without releasing any growth promoting substance. An intimate contact between both microorganisms was necessary for significant algal growth enhancement. The possibility of algal growth stimulation by bacterial attenuation of photosynthetic oxygen tension was indirectly examined by simulating the effect of bacteria through a physical removal of oxygen (air suction). Vacuum-treated cultures showed an increase in growth rate and photosynthetic activity as compared to the control, a result which cannot be explained by differences in CO2/HCO3− pump activity. In the presence of P. diminuta, the photosynthetic activity of S. bicellularis was more strongly stimulated under a limited concentration of inorganic carbon. It is suggested that, apart from a CO2 supply, aerobic bacteria can promote algal growth by reducing the photosynthetic oxygen tension within the microenvironment of the algal cells, thereby creating more favorable conditions for optimal photosynthetic algal growth.
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.
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 | 0.001 | 0.000 |
| 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".