Rethinking microbial infallibility in the metagenomics era
Bibliographic record
Abstract
The 'principle of microbial infallibility' was a mainstay of microbial physiology and environmental microbiology in earlier decades. This principle asserts that wherever there is an energetic gain to be made from environmental resources, microorganisms will find a way to take advantage of the situation. Although previously disputed, this claim was revived with the discovery of anammox bacteria and other major contributors to biogeochemistry. Here, we discuss the historical background to microbial infallibility, and focus on its contemporary relevance to metagenomics. Our analysis distinguishes exploration-driven metagenomics from hypothesis-driven metagenomics. In particular, we show how hypothesis-driven metagenomics can use background assumptions of microbial infallibility to enable the formulation of hypotheses to be tested by enrichment cultures. Discoveries of comammox and the anaerobic oxidation of methane are major instances of such strategies, and we supplement them with outlines of additional examples. This overview highlights one way in which metagenomics is making the transition from an exploratory data-analysis programme of research to a hypothesis-testing one. We conclude with a discussion of how microbial infallibility is a heuristic with far-reaching implications for the investigation of life.
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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 | 0.101 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.027 |
| Scholarly communication | 0.013 | 0.026 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.004 | 0.015 |
| 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".