jMIR and ACE XML: Tools for Performing and Sharing Research in Automatic Music Classification
Bibliographic record
Abstract
This presentation will begin by introducing the research fields of music information retrieval and automatic music classification. The core of the presentation will then be divided into two parts, the first dealing with the jMIR software suite, and the second dealing with the ACE XML file formats. jMIR is a set of free and open source software tools for automatically classifying music in a variety of ways. ACE XML is set of XML-based standardized file formats for storing and sharing the essential information that is related to automatic music classification. Although ACE XML is supported by each of the jMIR components, it is intended for use as a general standard in automatic music classification, and is not limited specifically to jMIR.
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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 | 0.029 | 0.079 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.017 | 0.012 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.012 | 0.014 |
| Open science | 0.010 | 0.012 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.050 | 0.043 |
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".