{"id":"W2003899524","doi":"10.1117/12.812377","title":"Musician Map: visualizing music collaborations over time","year":2008,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Music and Audio Processing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Timeline; Visualization; Computer science; Musical; Node (physics); Data visualization; World Wide Web; Plug-in; Information visualization; Multimedia; Visual arts; Data mining; Art; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005234819,0.0003437525,0.0004501024,0.0001508719,0.0002866847,0.0002478773,0.00167534,0.000182625,0.00002869804],"category_scores_gemma":[0.0003301148,0.0003009385,0.0004938084,0.0008273215,0.0002720465,0.001465995,0.0003617004,0.0002944113,0.000009381268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000155773,"about_ca_system_score_gemma":0.0001142199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007671694,"about_ca_topic_score_gemma":1.547717e-7,"domain_scores_codex":[0.9973602,1.960957e-8,0.0007202807,0.000530342,0.0009009211,0.0004882505],"domain_scores_gemma":[0.9973254,0.0001334788,0.0004773924,0.0001010984,0.001808853,0.0001537935],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001982181,0.0001327674,0.0001978284,0.0002545212,0.0002188583,4.144799e-7,0.0009336183,0.0000807394,0.4295875,0.5354646,0.03262563,0.0004836755],"study_design_scores_gemma":[0.004858917,0.001003543,0.005458735,0.001684534,0.0003703068,0.00019133,0.001908742,0.5338344,0.3560981,0.01025303,0.08173061,0.002607673],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903049,0.0001208187,0.001162691,0.003593014,0.0003742659,0.0004039864,0.00002250601,0.0001963743,0.003821376],"genre_scores_gemma":[0.5073827,0.00009179176,0.4876344,0.001732597,0.001364465,0.0002057317,0.00001461728,0.0001175254,0.001456242],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5337537,"threshold_uncertainty_score":0.9999443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01786895538918507,"score_gpt":0.2359671946171681,"score_spread":0.218098239227983,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}