Correction to: The Montreal Cognitive Assessment (MoCA): updated norms and psychometric insights into adaptive testing from healthy individuals in Northern Italy
Bibliographic record
Abstract
In the original version of this article, some typos regarding the adjustment coefficients for raw MoCA-Visuo-spatial (MoCA-VS) and MoCA-Attention (MoCA-A) scores (Table 3) were present and have now been amended (amended MoCA-VS cell: age=35, education=8; amended MoCA-A cells: age=55, education=8; age=35, education=13). Moreover, some imprecisions regarding the discussion of the discrepancies between the present and previous normative studies have been amended (page 379, Discussion: "More specifically, ESs allotments here reported proved to be stricter than those of Santangelo et al.’s [1] with regard to MoCA-total, -VS, -EF and -A, whereas less strict with regard to MoCA-O and Conti et al.’s [2] total"). We are thankful to the Researcher that has drawn our attention on such elements. The updated Table 3 is below: (Table presented.) Adjustment grids according to age and education for MoCA total and subtest raw scores Sub-test Education Age 35 40 45 50 55 60 65 70 75 80 85 90 95 Total 5 ...
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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 | 0.006 | 0.129 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.121 | 0.049 |
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".