Strict 2-Surface Proximal Classification of Knee-joint Vibroarthrographic Signals
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Bibliographic record
Abstract
Externally detected vibroarthrographic (VAG) signals contain information that can be used to characterize certain pathological aspects of the knee joint. To classify VAG signals as normal or abnormal, we propose to apply both the linear and nonlinear strict 2-surface proximal (S2SP) classifiers based on statistical parameters derived from VAG signals and selected by using a genetic algorithm (GA). A database of VAG signals of 89 human knee joints (51 normal and 38 abnormal) was studied. The classification performance of the linear S2SP classifier reached 0.82 in terms of the area under the receiver operating characteristics curve (Az) and 74.2% in average classification accuracy with the leave-one-out (LOO) procedure. The classification performance of the nonlinear S2SP classifier reached 0.95 in Az value and 91.0% in average classification accuracy using the Gaussian kernel with the LOO procedure, and possessed good robustness around the selected kernel parameter.
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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 | 0.001 |
| 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