An ecological framework for microbial metabolites in the ocean ecosystem
Bibliographic record
Abstract
Abstract The ocean microbe‐metabolite network involves thousands of individual metabolites that encompass a breadth of chemical diversity and biological functions. These microbial metabolites mediate biogeochemical cycles, facilitate ecological relationships, and impact ecosystem health. While analytical advancements have begun to illuminate such roles, a challenge in navigating the deluge of marine metabolomics information is to identify a subset of metabolites that have the greatest ecosystem impact. Here, we present an ecological framework to distill knowledge of fundamental metabolites that underpin marine ecosystems. We borrow terms from macroecology that describe important species, namely “dominant,” “keystone,” and “indicator” species, and apply these designations to metabolites within the ocean microbial metabolome. These selected metabolites may shape marine community structure, function, and health and provide focal points for enhanced study of microbe‐metabolite networks. Applying ecological concepts to marine metabolites provides a path to leverage metabolomics data to better describe and predict marine microbial ecosystems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".