Interactions between plant hormones and light quality signaling in regulating the shoot growth of<i>Arabidopsis thaliana</i>seedlings
Bibliographic record
Abstract
The effects of a decrease in red to far-red (R/FR) ratio on shoot growth of two-week-old Arabidopsis thaliana (L.) Heynh. seedlings were examined in the context of possible causal involvement of key plant growth hormones. Decreasing the R/FR ratio significantly increased petiole elongation and leaf area expansion of the Columbia (Col) line seedlings. In contrast, seedlings of the Landsberg erecta (Ler) line showed no significant change in leaf area and only a marginal increase in petiole growth. This low R/FR ratio-induced growth was accompanied by significant increases in concentrations of the growth “effector” gibberellin (GA4) and an auxin (indole-3-acetic acid (IAA)) in shoot tissues of Col. However, cytokinins (CKs) in Col shoot tissues were decreased and ethylene evolution was reduced when the R/FR ratio was decreased from that of normal sunlight to a low R/FR ratio. Several A. thaliana genotypes with plant hormone-related mutations were also assessed, including auxin resistant, axr2-1; GA insensitive, gai-1; and ethylene over-producing, eto2. None of these increased their petiole length or leaf area growth in response to lowering the R/FR ratio. We thus conclude that both GA4and IAA are causally involved in the increased shoot growth of A. thaliana Col seedlings that occurs in response to a lower than normal R/FR ratio.
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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) | 0.000 | 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 | 0.000 | 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".