Three-dimensional focal stack imaging in scanning transmission X-ray microscopy with an improved reconstruction algorithm
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Bibliographic record
Abstract
Focal stack (FS) is an effective technique for fast 3D imaging in high-resolution scanning transmission X-ray microscopy. Its crucial issue is to assign each object within the sample to the correct position along the optical axis according to a proper focus measure. There is probably information loss with previous algorithms for FS reconstruction because the old algorithms can only detect one focused object along each optical-axial pixel line (OAPL). In this study, we present an improved FS algorithm, which utilizes an elaborately calculated threshold for normalized local variances to extract multiple focused objects in each OAPL. Simulation and experimental results show its feasibility and high efficiency for 3D imaging of high contrast, sparse samples. It is expected that our advanced approach has potential applications in 3D X-ray microscopy for more complex samples.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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