Visualizing the fine structure and dynamics of living cells with temporal polychromatic digital holographic microscopy
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
Polychromatic digital holographic microscopy (P-DHM) has demonstrated its capacity to generate highly denoised optical path difference images, thereby enabling the label-free visualization of fine cellular structures, such as the dendritic arborization within neuronal cells in culture. So far, however, the sample must remain more or less stationary since P-DHM is performed manually, i.e., all actions are carried out sequentially over several minutes. In this paper, we propose fully automated, robust, and efficient management of the acquisition and reconstruction of the time series of polychromatic hologram sets, transforming P-DHM into temporal P-DHM. Experimental results have demonstrated the ability of the proposed temporal P-DHM implementation to non-invasively and quantitatively reveal the fine structure and dynamics of living cells.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it