Bibliographic record
Abstract
Trichomes, the unicellular hair-like projections found on the leaves of plants, present an ideal system for the study of cell fate and morphogenesis for biologists. They are easily accessible on the epidermis of plant leaves, they are good candidates for genetic manipulation, and they display easily identifiable mutant phenotypes. In addition to their utility as a model study system, trichomes have a variety of important functions in plants, including defence against insects and pathogens, reduction of water loss, and increased resistance to stress. This study will attempt to further characterize the trichome development pathway through the study of a mutant line of Arabidopsis thaliana that does not develop trichomes on its leaves. I hypothesize that one of the genes near the mutation site in pAG51 has decreased expression, and that this is the cause of the mutant’s trichome-less appearance. To test my hypothesis, I will first assess the transcript levels of the genes near the mutation site using a technique called Quantitative Polymerase Chain Reaction (QPCR). Once a gene has been identified, its function will be tested in vivo. The candidate gene will be knocked out in wild type A. thaliana, and if the progeny of this plant grow without trichomes, this will confirm the function of the candidate gene in trichome formation. Finally mutant pAG51 will be bred with another line of mutant A. thaliana, and the progeny phenotypes will be observed to understand how the candidate gene interacts with other genes in the trichome initiation pathway.
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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 | 0.001 | 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".