Importance of plant‐ and microbe‐driven metabolic pathways for plant defence
Bibliographic record
Abstract
Expression of plant phenotypes can depend on both plant genomes and interactions between plants and the microbes living in, on and near their roots. We understand a growing number of the mechanistic links between plant genotypes and phenotypes, such as defence against herbivory (see brief review in Hubbard et al., ), yet the links between root microbiomes and the comprehensive swathe of plant phenotypes they affect (Friesen et al., ) remain less clear. In this issue of Molecular Ecology, Hubbard et al. () follow microbe- and plant-driven changes in plant defence against hervibory from molecular underpinnings to ecological consequences, contrasting both the metabolites affected and the magnitude of defensive impact. Naively, we might expect plant genomes to drive more variation in phenotype than the root microbiome, but Hubbard et al. () find the opposite, implying profound consequences for plant trait evolution and ecological interactions.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.017 | 0.018 |
| Insufficient payload (model declined to judge) | 0.006 | 0.009 |
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".