Graphical analysis of flow cytometer data for characterizing controlled fluorescent protein display on λ phage
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As native virus particles typically cannot be resolved using a flow cytometer, the general practice is to use fluorescent dyes to label the particles. In this work, an attempt was made to use a common commercial flow cytometer to characterize a phage display strategy that allows for controlled levels of protein display, in this case, eGFP. To achieve this characterization, a number of data processing steps were needed to ensure that the observed phenomena were indeed capturing differences in the phages produced. Phage display of eGFP resulted in altered side scatter and fluorescence profile, and sub-populations could be identified within what would otherwise be considered uniform populations. Surprisingly, this study has found that side scatter may be used in the future to characterize the display of nonfluorescent proteins.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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 it