Clinical utility of the Czech version of Canadian Occupational Performance Measure for physiucally disabled adults patients
Bibliographic record
Abstract
Aim: The aim of diploma thesis was clinical utility of the Czech version of Canadian Occupational Performance Measure (COPM) in both parts. Utility in performance of activities of daily living and utility in satisfaction with performance of activities of daily living for physically disabled adults persons. Methods: The pre-research consisted of 40 persons with physical disability after stroke. For data collection was used Canadian Occupational Performance Measure, Barthel index and Subjective QUAlity of Life Analysis (SQUALA). Hypotheses were vitrificated by correlation analysis using Spearman's Rank Correlation Coefficient. Results: P-value (p = 0,00001) from the test of dependence of measured values by COPM in performance of activities of daily living and BI was lower than level of significance α = 0,05; 0,00001 < 0,05. P-value from the test of dependence of measured values by COPM in satisfaction with performance of activities of daily living and SQUALA questionnaire was lower than level of significant α = 0,05; 0,041 < 0,05. Conclusion: The results of the statistical analysis did not confirm the independence of the measured values by the Czech version COPM, BI and the SQUALA questionnaire. It was supported the using COPM in both parts, in performance of activities of daily living and in satisfaction...
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".