Modelling the auxin-mediated vein formation system in plant leaves
Bibliographic record
Abstract
The plant hormone auxin is involved in a wide range of developmental phenomena in plants.It carries out many of its effects through a signalling network involving the regulation of specific genes, including those involved in its own polar transport between cells.These transporters are able to be redistributed between cell faces, causing the asymmetric auxin transport that is a key requirement for the formation of vein patterns in leaves.In this thesis I describe the development of a biochemical kinetics-based model of auxin signalling and transport in a single cell, which displays biologically plausible responses to auxin application.The single-cell model then serves as the basis for a multicell model of auxin-mediated vein formation at a very early stage of leaf formation in Arabidopsis thaliana.I wish to thank my supervisor, Dr. Marc Roussel, for expressing his confidence by allowing me a remarkable degree of latitude in pursuing my project, for his constant support and guidance during both my undergraduate and graduate studies, and for his inspiring example as a scientist and teacher.Throughout my academic career, my family has provided sound foundations and constant support, for which I am very grateful.Dr. Steven Mosimann first convinced me that a graduate degree might be a good thing to pursue
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".