The Current Perception Threshold Test Differentiates Categories of Mechanical Neck Disorder
Bibliographic record
Abstract
= .6). Post hoc comparisons indicated differences between MND-I and MND-II (P = .05) and between MND-II and MND-III (P = .01), that were large effect sizes (MND I versus II, d = 1 and MND II versus III, d = 2.2). CPT testing was able to distinguish between MND II and III when a threshold value of greater than 11 was used to indicate MND-III. The predicted probability of abnormal CPT in MND-III had an estimated 73% sensitivity and 81% specificity; the odds ratio was 11.5 (P =.001) for the differentiation capacity of CPT between MND-II and III with a cut-off of 11. The area under the ROC curve (AUC) was .84 (95% CI =.72 to .96, P < .001). Conclusions CPT testing has moderate discriminatory accuracy, specificity, and sensitivity for classification of MND categories into neck pain with or without neurological signs. J Orthop Sports Phys Ther, Epub 10 May 2014. doi:10.2519/jospt.2014.5691.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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 source (direct Gemma or distilled Codex), 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".