Bibliographic record
Abstract
Objective: To investigate the feasibility and sensitivity of Montreal cognitive assessment( MoCA) and mini-mental state examination( MMSE) in the evaluation of mild cognitive impairment( MCI) in patients with chronic alcoholism( CA). Methods: The cognitive function of 60 patients with CA( CA group) and 30 healthy people( control group) were evaluated by MoCA and MMSE.Results: The differences of the scores of MoCA and MMSE between CA group and control group were statistically significant( P 0. 01). The differences of the visual space and memory and reaction abilities in two groups were statistically significant( P 0. 01).Conclusions: The federated applications of MoCA and MMSE are beneficial to find the MCI patients with CA in the early stage. The memory and sensitivity of the impairment in local cognitive domain evaluated by MoCA are better than MMSE. MoCA can provide an evidence for early finding,preventing and treating the cognitive impairment in patients with CA.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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 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".