Effects of cytokinin on ethylene production and nodulation in pea (<i>Pisum</i><i>sativum</i>) cv. Sparkle
Bibliographic record
Abstract
In this study, we were interested in learning if cytokinins play a role in the developmental process that leads to nodulation in the pea cv. Sparkle. We demonstrate that the application of the synthetic cytokinin BAP (6-benzyl-amino-purine) results in a number of nodulation-related changes. BAP stimulates the production of ethylene, a known inhibitor of nodulation. At low levels (up to 1 &mgr;M), BAP also stimulates nodulation but as its concentration is increased (up to 25 &mgr;M), nodule number decreases. In BAP-treated roots, the infection threads are abnormal; they are twisted, very knotty, and generally grow in a direction parallel to the root surface. In addition, the centers of cell division in the inner cortex are very few. Thus, BAP-treated Sparkle appears to phenocopy the low-nodulating pea mutant R50 [Guinel FC, Sloetjes LL (2000) Ethylene is involved in the nodulation phenotype of Pisum sativum R50 (sym 16), a pleiotropic mutant that nodulates poorly and has pale green leaves. J Exp Bot 51: 885-894]. However, it appears doubtful that there is a direct correlation between the actions of cytokinin and ethylene in causing a reduction in nodule organogenesis because nodulation is not restored by treating BAP-treated Sparkle with ethylene inhibitors.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".