ENVIRONMENTAL VISCOSITY DOES NOT AFFECT THE EVOLUTION OF COOPERATION DURING EXPERIMENTAL EVOLUTION OF COLICIGENIC BACTERIA
Bibliographic record
Abstract
Cooperation should be favored under environmental conditions allowing the preferential interaction of cooperators among themselves and limiting interactions with defectors. Bacteria cooperating to kill competitors by secreting a toxin evolved during several hundred generations in two environments: a viscous environment that should promote cooperator assortment, and a nonviscous environment that should not allow such preferential interaction. A quantitative decrease in cooperation was observed in all populations, but as expected, cooperation was maintained at a higher level in the viscous environment. Mutants that are resistant against but not producing the toxin were identified at a low frequency in a few populations from the viscous environment and at a high frequency in all the populations from the nonviscous environment. The underlying mutations were identified. Relative fitness of the cooperator and mutant genotypes were obtained with bacteria that were isogenic, except for the identified mutations. Competition experiments indicated that cooperation is not favored by environmental viscosity as imposed in our system and suggested that when it comes to cooperation, environmental viscosity should be considered not only in terms of individual movement, but also in terms of the distribution of the public good.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".