Bibliographic record
Abstract
Hormones are chemical substances that can affect many cellular and developmental processes at low concentrations. Plant hormones co-ordinate growth and development at almost all stages of the plant's life cycle by integrating endogenous signals and environmental cues. Much debate in hormone biology revolves around specificity and redundancy of hormone signalling. Genetic and molecular studies have shown that these small molecules can affect a given process through a signalling pathway that is specific for each hormone. However, classical physiological and genetic studies have also demonstrated that the same biological process can be regulated by many hormones through independent pathways (co-regulation) or shared pathways (cross-talk or cross-regulation). Interactions between hormone pathways are spatiotemporally controlled and thus can vary depending on the stage of development or the organ being considered. In this chapter we discuss interactions between abscisic acid, gibberellic acid and ethylene in the regulation of seed germination as an example of hormone cross-talk. We also consider hormone interactions in response to environmental signals, in particular light and temperature. We focus our discussion on the model plant Arabidopsis thaliana.
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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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".