Validity of the Montreal Battery of Evaluation of Amusia: An Analysis Using Structural Equation Modeling
Bibliographic record
Abstract
The Montreal Battery of Evaluation of Amusia (MBEA) is the gold standard for diagnosing amusia.We aimed to evaluate its factorial and convergent validity.Data were collected for the MBEA and a self-report Amusic Dysfunction Inventory on a non-random sample (n = 249), and the following Structural Equation Modeling (SEM) procedures were conducted: confirmatory factor analysis of the theoretical model; exploratory SEM for alternative non-restricted factor solutions; and structural models with each of these solutions as predictors of the inventory's items.The theoretical model did not prove acceptable goodness of fit, and two-and threefactor non-restricted models were better-fitted solutions for Scale, Contour and Interval tests, and Meter and Memory tests, respectively, than the theoretical one-factor model.This may reflect distinct perceptua l processes rela ted to neurocognitive demand.The non-restricted models of Scale, Meter and Memory showed to be acceptable predictors of self-reported capacity for melodic perception, vocal production, rhythmic coordination, and memory.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.027 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".