Musician Map: visualizing music collaborations over time
Bibliographic record
Abstract
In this paper we introduce Musician Map, a web-based interactive tool for visualizing relationships among popular musicians who have released recordings since 1950. Musician Map accepts search terms from the user, and in turn uses these terms to retrieve data from <i>MusicBrainz.org</i> and <i>AudioScrobbler.net</i>, and visualizes the results. Musician Map visualizes relationships of various kinds between music groups and individual musicians, such as band membership, musical collaborations, and linkage to other artists that are generally regarded as being similar in musical style. These relationships are plotted between artists using a new timeline-based visualization where a node in a traditional node-link diagram has been transformed into a Timeline-Node, which allows the visualization of an evolving entity over time, such as the membership in a band. This allows the user to pursue social trend queries such as "Do Hip-Hop artists collaborate differently than Rock artists".
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".