Reshaping graduate outcomes of science students – The contribution of undergraduate research experiences
Bibliographic record
Abstract
Confocal microscopy has several advantages over wide-field microscopy, such as out-of-focus light suppression, 3D sectioning, and compatibility with specialized detectors. While wide-field microscopy is a faster approach, multiplexed confocal schemes can be used to make confocal microscopy more suitable for high-throughput applications, such as high-content screening (HCS) commonly used in drug discovery. An increasingly powerful modality in HCS is fluorescence lifetime imaging microscopy (FLIM), which can be used to measure protein-protein interactions through Förster resonant energy transfer (FRET). FLIM-FRET for HCS combines the requirements of high throughput, high resolution and specialized time-resolving detectors, making it difficult to implement using wide-field and spinning disk confocal approaches. We developed a novel foci array scan method that can achieve uniform multiplex confocal acquisition using stationary lenslet arrays for high resolution and high throughput FLIM. Unlike traditional mirror galvanometers, which work in Fourier space between scan lenses, this scan method uses optical flats to steer a 2-dimension foci array through refraction. After integrating this scanning scheme in a multiplexing confocal FLIM system, we demonstrate it offers clear benefits over traditional mirror galvanometer scanners in scan linearity, uniformity, cost and complexity.
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How this classification was reachedexpand
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 | 0.024 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.017 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".