Too much of a good thing? Hybrid necrosis as a by-product of plant immune system diversification
Bibliographic record
Abstract
Plants defend themselves against their enemies with an impressive arsenal of physical barriers, surveillance and defense proteins, enzymes, and toxic chemicals. Many different molecules are involved in the detection of invaders, suggesting that pathogen pressure selects for a broad array of defense strategies and a high diversity of recognition specificities in host species. Recent results in plants, however, show that immune system diversification can also have negative consequences; epistatic interactions among divergent immune system components can cause hybrid necrosis, a form of genetic incompatibility. This type of hybrid failure is frequently lethal, and characterized by the widespread induction of programmed cell death leading to tissue necrosis. In characterized examples, this is caused by hyperactivation of defense responses. Both the prevalence of hybrid necrosis in diverse plant taxa, and the growing indication that it may arise as a by-product of adaptation to the biotic environment, emphasize that it is likely a general factor in plant evolution. Since hybrid necrosis negatively impacts the progeny of certain crosses, divergence of the plant immune system may indirectly affect gene flow among populations, and perhaps contribute to the establishment or maintenance of species barriers.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".