The data of Gause on interaction of two species of yeast: Lotka-Volterra’s interspecific competition or product inhibition?
Bibliographic record
Abstract
An examination is made of the growth and interaction of two alcohol producing species of yeast, Schizosaccharomyces "Kephir ” and Saccharomyces cerevisiae in both monoculture and mixture as reported by Gause (1934. The struggle for existence. Williams and Wilkins, Baltimore, M.D.) and modeled by de Wit and Goudriaan (1978. Simulation of ecological processes. A Halsted Press Book. John Wiley & Sons, New York, Toronto.), on the basis of Lotka-Volterra competition model. The logistic equation of growth has been integrated to represent the inhibition of growth of each species by alcohol in pure culture. This model is expanded for mixed culture, based on the relative inhibition of each species by the other. The proposed model for pure anaerobic culture produces results identical to Lotka-Volterra model for both organisms. For mixed culture, the model shows that both species reach the potential levels expected by the model. However, the relative growth rates of the two organisms are affected differently, one, (Kephir), behaves exactly according to the model, and theother, (S.cerevisiae), exhibits considerable reduction in relative growth rate. This interaction also confirms the general conclusion of de Wit & Goudriaan that in addition to alcohol, some other factor must be involved in mixed culture of the two species..
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".