Plant bioactive peptides: an expanding class of signaling molecules
Bibliographic record
Abstract
Until recently, our knowledge of intercellular signaling in plants was limited to the so-called five classical plant hormones: auxin, cytokinin, gibberellin, ethylene, and abscissic acid. Other chemical compounds like sterols and lipids have also been recognized as signaling molecules in plants, but it was only recently discovered that peptides in plants, as in animal cells, play crucial roles in various aspects of growth and development, biotic and abiotic stress responses, and self/non-self recognition in sporophytic self-incompatibility. These peptides are often part of a very large gene family whose members show diverse, sometime overlapping spatial and temporal expression patterns, allowing them to regulate different aspects of plant growth and development. Only a handful of peptides have been linked to a bona fide receptor, thereby activating a cascade of events. Since these peptides have been thoroughly reviewed in the past few years, this review will focus on the small putative plant signaling peptides, some often disregarded in the plant peptide literature, which have been shown through biochemical or genetic studies to play important roles in plants.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".