Reduction of doubtful detection of micro-nucleus in human lymphocyte
Why this work is in the frame
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Bibliographic record
Abstract
The image correction is proposed by evaluating the Point-Spread Function (PSF) of Wiener's deconvolution for motion blur and Gaussian out of focus alterations. It permits to reduce the number of rejected images for the detection of Micro Nucleuses into lymphocyte images. It operates in conjunction with spatial filters, pointed out to correct bad exposure, Gaussian out of focus and noise. The heavy computation burden suggests to use the Wiener's deconvolution to process the rejected images from spatial filters. To speed-up the correction, the implementation is based on computing distributed service. The criteria to establish the number of PCs is evaluated. This is an expanded version of a paper presented at the 3rd IEEE International Workshop on Medical Measurements and Applications, 9?10 May 2008, Ottawa, ON, Canada.
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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 | 0.000 |
| 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