{"id":"W4387446822","doi":"10.1145/3610661.3616183","title":"Combining Artificial Intelligence, Bio-Sensing and Multimodal Control for Bio-Responsive Interactives","year":2023,"lang":"en","type":"article","venue":"","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Gesture; Computer science; Human–computer interaction; Process (computing); Entrainment (biomusicology); Synchronization (alternating current); Natural (archaeology); Artificial intelligence; Channel (broadcasting); Rhythm","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":[0.0005777359,0.0004859141,0.0003686141,0.0004201563,0.0003528698,0.001293959,0.001147115,0.000718827,0.005469887],"category_scores_gemma":[0.0007066113,0.000175471,0.0004107393,0.0001924685,0.0006623865,0.0010999,0.001271474,0.0005751323,0.001213897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003280412,"about_ca_system_score_gemma":0.0003510155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000633037,"about_ca_topic_score_gemma":0.0006736019,"domain_scores_codex":[0.9995291,0.00008927624,0.00002862115,0.0001127422,0.0001926053,0.00004768902],"domain_scores_gemma":[0.9997652,0.0000817752,0.00001588655,0.00003979844,0.00005675536,0.00004066084],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003162018,0.0004156799,0.001469169,0.0008176679,0.0001575698,0.000959558,0.001685807,0.01202474,0.5595439,0.0541679,0.005632197,0.3628098],"study_design_scores_gemma":[0.0001245255,0.002039492,0.00677581,0.0003575199,0.0003092389,0.002948755,0.0006477801,0.338657,0.3841316,0.06474357,0.1989986,0.0002661298],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0181565,0.0006218621,0.9676856,0.0003646777,0.00007378167,0.0002187192,0.00005953509,0.003260589,0.009558759],"genre_scores_gemma":[0.4301204,0.0008655867,0.5539837,0.0004166042,0.0001078404,0.0004237504,0.0001728647,0.000270369,0.01363881],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005469887,"threshold_uncertainty_score":0.01829863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05695689226005194,"score_gpt":0.3322528856424172,"score_spread":0.2752959933823653,"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."}}