Supplementary material from "The ecology of scale: impact of volume on coalescence and function in methanogenic communities"
Bibliographic record
Abstract
Engineered ecosystems span multiple volume scales, from a nano-scale to thousands of cubic meters. Even the largest industrial systems are tested in pilot scale facilities. But does scale affect outcomes? Here we look at comparing different size laboratory anaerobic fermentors to see if and how the volume of the community affects the outcome of community coalescence (combining multiple communities) on community composition and function. Our results show that there is an effect of scale on biogas production. Furthermore, we see a link between community evenness and volume, with smaller scale communities having higher evenness. Despite those differences, the overall patterns of community coalescence are very similar at all scales, with coalescence leading to levels of biogas production comparable with that of the best-performing component community. The increase in biogas with increasing volume plateaus, suggesting there is a volume where productivity stays stable over large volumes. Our findings are reassuring for ecologists studying large ecosystems and industries operating pilot scale facilities, as they support the validity of pilot scale studies in this field.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.895 | 0.594 |
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".