Bibliographic record
Abstract
In order to carry out its life cycle and produce viable progeny through cell division, a cell must successfully coordinate and execute a number of complex processes with high fidelity, in an environment dominated by thermal noise. One important example of such a process is the assembly and positioning of the mitotic spindle prior to chromosome segregation. The mitotic spindle is a modular structure composed of two spindle pole bodies, separated in space and spanned by filamentous proteins called microtubules, along which the genetic material of the cell is held. The spindle is responsible for alignment and subsequent segregation of chromosomes into two equal parts; proper spindle positioning and timing ensure that genetic material is appropriately divided amongst mother and daughter cells. In this thesis, I describe fluorescence confocal microscopy and automated image analysis algorithms, which I have used to observe and analyze the real space dynamics of the mitotic spindle in budding yeast. The software can locate structures in three spatial dimensions and track their movement in time. By selecting fluorescent proteins which specifically label the spindle poles and cell periphery, mitotic spindle dynamics have been measured in a coordinate system relevant to the cell division. I describe how I have characterised the accuracy and precision of the algorithms by simulating fluorescence data for both spindle poles and the budding yeast cell surface. In this thesis I also describe the construction of a microfluidic apparatus that allows for the measurement of long time-scale dynamics of individual cells and the development of a cell population. The tools developed in this thesis work will facilitate in-depth quantitative analysis of the non-equilibrium processes in living cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".