{"id":"W4307174479","doi":"10.5281/zenodo.7243950","title":"Interactive Sonification for Health and Energy using ChucK and Unity","year":2022,"lang":"en","type":"paratext","venue":"arXiv (Cornell University)","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Sonification; Energy (signal processing); Human–computer interaction; Computer science; Multimedia; Physics","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":[0.00151345,0.0009330666,0.0005741738,0.001186637,0.0004724922,0.0016815,0.001638455,0.0009608851,0.01585591],"category_scores_gemma":[0.006646057,0.0003833853,0.0009544157,0.0005752902,0.001109101,0.002298095,0.005032075,0.001015235,0.002744288],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004886856,"about_ca_system_score_gemma":0.0006663018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001524676,"about_ca_topic_score_gemma":0.002291565,"domain_scores_codex":[0.9991661,0.000220861,0.00007153654,0.0001734735,0.0002727521,0.00009525637],"domain_scores_gemma":[0.9979241,0.001369443,0.00007555316,0.0002706901,0.0002110796,0.0001491123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002510184,0.0002649897,0.003420119,0.001761213,0.0001859417,0.001667436,0.008987259,0.03603343,0.1461966,0.08207591,0.04065898,0.6762379],"study_design_scores_gemma":[0.0003904889,0.000722346,0.006336807,0.0005009986,0.0001659958,0.002182822,0.002307829,0.3483636,0.1538036,0.1012598,0.3835819,0.0003838894],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01439902,0.0003206151,0.9513189,0.0002872515,0.0001063003,0.0002049027,0.0006441455,0.02500362,0.007715263],"genre_scores_gemma":[0.2536006,0.0005154968,0.7227734,0.0004155522,0.0001046481,0.001007815,0.002722442,0.004148171,0.01471188],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01585591,"threshold_uncertainty_score":0.05304331,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1643712745646848,"score_gpt":0.2639550119478509,"score_spread":0.09958373738316612,"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."}}