{"id":"W4400015627","doi":"10.14236/ewic/eva2024.53","title":"Curves and Reverbs: A Wearable to Sound Participatory Performance","year":2024,"lang":"en","type":"article","venue":"Electronic workshops in computing","topic":"Music Technology and Sound Studies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Wearable computer; Computer science; Sound (geography); Participatory sensing; Citizen journalism; Human–computer interaction; Acoustics; Data science; World Wide Web; Embedded system; Physics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008977956,0.0001395908,0.0001896126,0.0001550369,0.0002021947,0.000121145,0.000405365,0.00006920174,0.000004717305],"category_scores_gemma":[0.00006961574,0.0001337323,0.00002642991,0.0008716185,0.00006041117,0.000213242,0.0004263503,0.0005221303,0.00002615652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001156966,"about_ca_system_score_gemma":0.00009786898,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006616255,"about_ca_topic_score_gemma":0.00005461586,"domain_scores_codex":[0.9984603,0.00005249544,0.0002197946,0.0004659116,0.0001327191,0.000668762],"domain_scores_gemma":[0.9993801,0.0002425068,0.00002284102,0.0002918466,0.00001728496,0.00004538785],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001592183,0.00009081022,0.01781303,0.0008327424,0.0001404976,0.00009762665,0.01417439,0.003131222,0.00008365967,0.2312584,0.0122034,0.7201583],"study_design_scores_gemma":[0.0004203982,0.0003846624,0.01624651,0.005609155,0.00002438129,0.0001534856,0.0002701567,0.8915527,0.0002391457,0.04551202,0.0386508,0.0009365879],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8104537,0.05722075,0.1265695,0.003680994,0.0003889543,0.0001899981,1.381566e-7,0.0005042919,0.0009916644],"genre_scores_gemma":[0.995657,0.0009268192,0.00230904,0.0007787675,0.00006256434,0.00001824427,1.693172e-7,0.000008527319,0.0002389232],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8884215,"threshold_uncertainty_score":0.5453444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02120059020763864,"score_gpt":0.278262539697577,"score_spread":0.2570619494899383,"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."}}