{"id":"W2989681992","doi":"10.4000/volume.7254","title":"Hacking Jeff Minter’s Virtual Light Machine: Unpacking the Code and Community Behind an Early Software-Based Music Visualizer","year":2019,"lang":"en","type":"article","venue":"Volume !","topic":"Music Technology and Sound Studies","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Musée de la Civilisation","funders":"","keywords":"Computer science; Hacker; Code (set theory); Software; Multimedia; Visualization; World Wide Web; Artificial intelligence; Computer security; Programming language","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001831577,0.0004011428,0.0002168381,0.001531706,0.007962191,0.008777885,0.0007264363,0.001910003,0.005995488],"category_scores_gemma":[0.008050065,0.0004060489,0.0001547041,0.000890589,0.01237205,0.01037393,0.004646488,0.004056541,0.001493923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002251967,"about_ca_system_score_gemma":0.001381217,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004524835,"about_ca_topic_score_gemma":0.008992621,"domain_scores_codex":[0.9982401,0.0007462577,0.00004846944,0.0002531729,0.0004817644,0.0002302564],"domain_scores_gemma":[0.9959688,0.002361346,0.0002870813,0.0003513015,0.0005083968,0.0005231024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00006175652,0.00008057182,0.002873364,0.0001632932,0.000008922447,0.0007032966,0.2759604,0.0001332056,0.002501496,0.3765415,0.2155865,0.1253858],"study_design_scores_gemma":[0.000006873342,0.0000616118,0.001828814,0.000251504,0.000006687116,0.0009124537,0.05001446,0.0003591813,0.001774503,0.02454522,0.9202099,0.00002882129],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2646671,0.01689424,0.03566759,0.2093687,0.004221052,0.0001097141,0.0001028267,0.001165441,0.4678034],"genre_scores_gemma":[0.7479247,0.009836907,0.01232779,0.02312508,0.001485564,0.0001186689,0.00006031964,0.001238656,0.2038823],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008777885,"threshold_uncertainty_score":0.0200569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0203682622805118,"score_gpt":0.2494990073338204,"score_spread":0.2291307450533086,"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."}}