Evaluation of texture parameters for the quantitative description of multimodal nonlinear optical images from atherosclerotic rabbit arteries
Bibliographic record
Abstract
The composition and structure of atherosclerotic lesions can be directly related to the risk they pose to the patient. Multimodal nonlinear optical (NLO) microscopy provides a powerful means to visualize the major extracellular components of the plaque that critically determine its structure. Textural features extracted from NLO images were investigated for their utility in providing quantitative descriptors of structural and compositional changes associated with plaque development. Ten texture parameters derived from the image histogram and gray level co-occurrence matrix were examined that highlight specific structural and compositional motifs that distinguish early and late stage plaques. Tonal-texture parameters could be linked to key histological features that characterize vulnerable plaque: the thickness and density of the fibrous cap, size of the atheroma, and the level of inflammation indicated through lipid deposition. Tonal and texture parameters from NLO images provide objective metrics that correspond to structural and biochemical changes that occur within the vessel wall in early and late stage atherosclerosis.
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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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".