<scp>GAL4</scp> / <scp>GFP enhancer‐trap</scp> lines for identification and manipulation of cells and tissues in developing Arabidopsis leaves
Bibliographic record
Abstract
BACKGROUND: Understanding developmental processes requires the unambiguous identification of cells and tissues, and the selective manipulation of the properties of those cells and tissues. Both requirements can most efficiently be satisfied through the use of GAL4/GFP enhancer-trap lines. No such lines, however, have been characterized for the study of early leaf development in the Columbia-0 reference genotype of Arabidopsis. RESULTS: Here we address this limitation by identifying and characterizing a set of GAL4/GFP enhancer-trap lines in the Columbia-0 background for the specific labeling of cells and tissues during early leaf development, and for the targeted expression of genes of interest in those cells and tissues. CONCLUSIONS: By using one line in our set to address outstanding questions in leaf vein patterning, we show that these lines can be used to address key questions in plant developmental biology.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".