Combinatorial interaction network of transcriptomic and phenotypic responses to nitrogen and hormones in the <i>Arabidopsis thaliana</i> root
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Plants form the basis of the food webs that sustain animal life. Exogenous factors, such as nutrients and sunlight, and endogenous factors, such as hormones, cooperate to control both the growth and the development of plants. We assessed how Arabidopsis thaliana integrated nutrient and hormone signaling pathways to control root growth and development by investigating the effects of combinatorial treatment with the nutrients nitrate and ammonium; the hormones auxin, cytokinin, and abscisic acid; and all binary combinations of these factors. We monitored and integrated short-term genome-wide changes in gene expression over hours and long-term effects on root development and architecture over several days. Our analysis revealed trends in nutrient and hormonal signal crosstalk and feedback, including responses that exhibited logic gate behavior, which means that they were triggered only when specific combinations of signals were present. From the data, we developed a multivariate network model comprising the signaling molecules, the early gene expression modulation, and the subsequent changes in root phenotypes. This multivariate network model pinpoints several genes that play key roles in the control of root development and may help understand how eukaryotes manage multifactorial signaling inputs.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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 it