{"id":"W2140493473","doi":"10.5281/zenodo.1177470","title":"Sharing Data In Collaborative, Interactive Performances : The Senseworld Datanetwork","year":2009,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Music Technology and Sound Studies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Concordia University","funders":"","keywords":"Computer science; Process (computing); Multimedia; Interactive media; Human–computer interaction; Data sharing; Collaborative software; World Wide Web; Operating system","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":[0.003275538,0.0009010581,0.0007376479,0.001046295,0.002044622,0.00822823,0.004751139,0.002150537,0.01628145],"category_scores_gemma":[0.008081787,0.0009926982,0.001030808,0.002326492,0.002243708,0.01173802,0.00757428,0.002979446,0.006523071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001621467,"about_ca_system_score_gemma":0.002677157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006001499,"about_ca_topic_score_gemma":0.007102086,"domain_scores_codex":[0.9961476,0.000735575,0.0003458781,0.0006876374,0.001639058,0.0004440873],"domain_scores_gemma":[0.9950569,0.0006704291,0.0001491166,0.002299471,0.0006903532,0.00113381],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001693984,0.0005976554,0.004760485,0.001838512,0.0001225088,0.0007827136,0.002264278,0.02885831,0.0157705,0.4440982,0.1796214,0.3195914],"study_design_scores_gemma":[0.0001324516,0.0001998439,0.0007191406,0.0002096728,0.00005602705,0.0007282174,0.0005466031,0.08753365,0.01571509,0.08544762,0.8085505,0.0001611974],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01417383,0.001451942,0.8862771,0.003453043,0.0006121537,0.001641024,0.00660628,0.03381329,0.05197135],"genre_scores_gemma":[0.2906396,0.003757767,0.56419,0.00129624,0.0004062872,0.003459988,0.04103198,0.009922312,0.08529578],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01628145,"threshold_uncertainty_score":0.0544669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04431039980536933,"score_gpt":0.2749601791901358,"score_spread":0.2306497793847665,"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."}}