The montreal protocol for identification of amusia
Bibliographic record
Abstract
The Montreal Battery for the Evaluation of Amusia (MBEA; Peretz, Champod, & Hyde, 2003) is an empirically-grounded quantitative tool that is widely used to identify individuals with congenital amusia. The use of such a standardized measure ensures that individuals tested conform to a specific neuropsychological profile, allowing for comparisons across studies and research groups. Recently, a number of researchers have published credible critiques of the usefulness of the MBEA as a diagnostic tool for amusia. Here we argue that the MBEA and its online counterpart, the AMUSIA tests (Peretz et al., 2008), should be considered steps in a screening process for amusia, rather than standalone diagnostic tools. The goal of this article is to present, in detailed and easily replicable format, the full protocol with which congenital amusics should be identified. In providing information that often goes unreported in published articles, we aim to clarify the strengths and limitations of the MBEA, and make recommendations for its continued use by the research community as part of the Montreal Protocol for Identification of Amusia (MPIA).
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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 | 0.038 | 0.121 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.136 | 0.055 |
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".