RESEARCH PAPER<br>Identification and characterization of genes connectedwith flower morphogenesis in cucumber
Bibliographic record
Abstract
Sex determination and flower morphogenesis are very broad and complex processes controlled at many levels. Four clones have been isolated from cucumber transcriptomes, mapped onto the cucumber genome and checked if the corresponding genes expression differed between the vegetative and generative tissues (leaf, shoot apex, and 1- to 2-mm flower buds) of monoecious and gynoecious cucumber lines. To determine the role, and characteristics of identified genes in flower morphogenesis, as well as to understand the flower reproduction in cucumber, comprehensive computational studies using upstream regulatory elements and protein motifs were performed. A genome-wide overview of cucumber clones revealed that sequence of only one clone was mapped in the coding site. The gene was described as CsPSTK1 encoding serine/threonine kinase. The results allow us to conclude that cucumber generative organs differ in responsiveness to plant hormones due to the distinct signal transductions that are mediated by protein kinases in male and female organs of the floral buds and shoot apices. Protein kinases may be an alternative way for hormonal signal transduction in flowers of the opposite sex, taking part in the inhibition of unwanted generative organs that cause the development of a unisex flower.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".