Web-based Testing of Congenital Amusia with the <i>Montreal Battery of Evaluation of Amusia</i>
Bibliographic record
Abstract
In this article we present the results of a web-based testing of 117German undergraduate students with the Montreal Battery of Evaluation of Amusia (MBEA; Peretz et al. 2003). The MBEA is used to assess congenital amusia, a neuro-developmental disorder present in approximately 4% of the population, according to Kalmus & Fry(1980). Recently, criticism has arisen concerning the usage of the MBEA in relation to the prevalence of congenital amusia in the general population and the statistical evaluation of the results (Henry& McAuley, 2010; 2013, Pfeifer & Hamann 2015).We compare the results of our web-based study to a group of 111German students that was tested with a computer-implemented MBEA version under laboratory conditions (Pfeifer & Hamann 2015).We found significant differences between the web-based and the laboratory group based on their sum of correct responses. A Signal Detection Theory analysis of the data, which factors out response bias, however, shows that the discriminatory ability of both groups seems to be fairly similar. The results of the current study are used to critically discuss the validity of a web-based MBEA specifically butal so web-based testing more generally as a means of diagnosing congenital amusia.
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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 | 0.003 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".