Perbedaan Skor INA-MOCA pada Pemain Catur dan Bukan Pemain Catur
Bibliographic record
Abstract
Abstract: Aging is progressive declining process of many body functions, including cognitive function. Cognitive function is a conscious mental activity such as thinking, memory, learning, as well as language, and can be evaluated by using INA-MoCA. Chess is a popular game that requires intelligence. Some researchers believe that there is a close relation between cognitive function and chess. This study was aimed to determine whether there was any difference between the cognitive function of chess players and non-chess player. This was an analytic study with a cross-sectional study. Primary data were obtained from INA-MoCA score of the chess players and non-chess players. The results showed that in non-elderly category, the average score of INA-MoCA indicated that chess players had higher cognitive functions than non-chess players (p=0.43). In elderly category, the average score of INA-MoCA indicated that the chess players had better cognitive function than the non-chess players by 2.77 (p=0.03). Conclusion: Either elderly or non-elderly, chess players had higher cognitive function than non-chess players.Keywords: cognitive function, elder, chess, INA-MoCA Abstrak: Menua adalah proses penurunan banyak fungsi tubuh yang progresif, termasuk penurunan kognitif. Fungsi kognitif adalah aktivitas mental secara sadar seperti berpikir, mengingat, belajar, dan bahasa. Salah satu evaluasi fungsi kognitif dengan menggunakan INA-MoCA. Permainan catur merupakan permainan yang populer dan memerlukan kecerdasan. Beberapa peneliti percaya bahwa ada hubungan yang erat antara fungsi kognitif dan permainan catur. Penelitian ini bertujuan untuk mengetahui apakah terdapat perbedaan fungsi kognitif antara pemain catur dan bukan pemain catur. Jenis penelitian ialah analitik dengan desain potong lintang. Data primer ialah skor INA-MoCA pemain catur dan bukan pemain catur. Hasil penelitian pada kelompok bukan lansia, rerata skor INA-MoCA mengindikasikan pemain catur memiliki fungsi kognitif yang lebih tinggi daripada yang bukan pemain catur (p=0,43). Pada kelompok lansia, rerata skor INA-MoCA menunjukan pemain catur memiliki fungsi kognitif yang lebih baik daripada bukan pemain catur dengan selisih 2,77 (p=0,03). Simpulan: Fungsi kognitif pemain catur baik pada lansia maupun bukan lansia lebih baik daripada bukan pemain catur.Kata kunci: fungsi kognitif, lansia, pemain catur, INA-MoCA
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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".