Plate analyzer - a yeast colony size measurement system
Bibliographic record
Abstract
Automated systems that can measure colony sizes (e.g. saccharomyces cerevisiae) are a useful tool for research in functional genomics, allowing for fast and convenient analyses. This motivated the previous development of an image analysis based, colony size measurement system called Growth Detector. In this paper, we introduce a new colony size measurement system called Plate Analyzer, which expands upon Growth Detector. This system is implemented in Octave and will be made freely available for non-commercial purposes. A new preprocessing method is presented, which removes the Growth Detector requirements of non-standardized markers that are used for scaling, alignment, and registration of plate images. Furthermore, the new system is able to analyze plates of arbitrary dimension and spotting pattern, facilitating its adoption by other research laboratories. Growth Detector's susceptibility to the effects of non-homogenous illumination is discussed and is motivating research into localized analysis of colony sizes. The enhancements in Plate Analyzer will enable more wide use of this system through its increased accessibility, while simultaneously improving upon the generalizability, accuracy, and robustness of the analysis.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.022 | 0.020 |
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".