The Roles of Cytokinins in Plants and Their Response to Environmental Stimuli
Bibliographic record
Abstract
Cytokinins (CKs) are adenine-derived, small-molecule plant growth regulators that control aspects of almost all plant growth and development processes. Internally, CKs play significant roles in plant cell division, nutrient allocation, and photosynthetic performance, and they are also detection and signaling agents for plant responses to the environmental challenges. CK functions in plant metabolism include plant adaptations to various abiotic stresses as well as their regulatory role in plant interactions with biotic components of the environment. Interestingly, CK biosynthesis is not exclusive to plants. New genetic and chemical approaches have revealed that both beneficial (symbiotic microorganisms) and detrimental (pathogenic bacteria, fungi, or insects) non-plant biota can secrete these phytohormones to purposefully modify plant metabolism. Therefore, while many open questions remain about how CKs are actively utilized by plants and plant-interacting organisms, CK roles should be seen more broadly, as signaling molecules for which effects range from within cells to as far as interkingdom relationships. The papers in this Special Issue highlight several aspects of CK biosynthesis, metabolism, and functions within plants and among plant-associated organisms, typifying the extensive range of roles played by these signaling molecules. The collection of papers represents new examples for CK researchers to consider advancing the growing range of topics related to how CKs mediate responses to many kinds of environmental stimuli and stresses.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.007 | 0.007 |
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".