Bibliographic record
Abstract
Objectives: The objective of this study was to evaluate the reliability and validity of Pattern Identifications Tool for Cognitive Disorders (PIT-C) and verify the correlation with other related scales. Methods: The study in this protocol is a single group, prospective, observational one. The subjects of the study were men and women between the ages of 45 and 85, diagnosed with neurocognitive disorders by Diagnostic and Statistical Manual of Mental Disorder (fifth Edition) criteria (n=60, Clinical Dementia Rating (CDR)=0.5, Korean Version of Montreal Cognitive Assessment (MoCA-K)≤22). The reliability of PIT-C was evaluated as test-retest and inter-rater reliability. And correlation between PIT-C and other related scales was also assessed. Results: This study was approved by the Institutional Review Board (IRB) of Dunsan Korean Medicine Hospital of Daejeon University and registered in the Clinical Research Information Service (CRIS), and was made public in advance to ensure transparency of the research process and conduct ethical clinical trials. Conclusions: The results of this study can be used to classify neurocognitive disorders as Korean medicine and PIT-C will be helpful tool for primary health care.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".