{"id":"W2593242293","doi":"10.1145/3025171.3025228","title":"Intelligent Sensory Modality Selection for Electronic Supportive Devices","year":2017,"lang":"en","type":"article","venue":"","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Modality (human–computer interaction); Modalities; Stimulus modality; Computer science; Task (project management); Sensory system; Human–computer interaction; Selection (genetic algorithm); Artificial intelligence; Cognitive psychology; Psychology; Engineering; Systems engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001854919,0.0008706179,0.0003319909,0.000502898,0.0004454141,0.001009519,0.0005888273,0.0005768333,0.002897515],"category_scores_gemma":[0.01288473,0.0002690355,0.0002805933,0.0001742728,0.000518528,0.001421132,0.001088037,0.0003589506,0.0003424098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000209361,"about_ca_system_score_gemma":0.0002943924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003138091,"about_ca_topic_score_gemma":0.0005773762,"domain_scores_codex":[0.9987862,0.0005986952,0.0001032498,0.000155024,0.0002671462,0.00008972018],"domain_scores_gemma":[0.9926534,0.005727509,0.0004531698,0.000430198,0.0005109918,0.000224691],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006589017,0.00224118,0.02373925,0.001564768,0.0001513084,0.0005269251,0.005148021,0.01078281,0.5525334,0.003013187,0.001069681,0.3926404],"study_design_scores_gemma":[0.002503442,0.03986318,0.2968974,0.0009503663,0.001190457,0.004185945,0.007296179,0.168297,0.4312508,0.02699388,0.01964342,0.0009279394],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9287605,0.0002851239,0.06712329,0.0001515036,0.00003120996,0.0002950902,0.00004230882,0.0003332245,0.002977568],"genre_scores_gemma":[0.9646935,0.00009658973,0.03454172,0.00006311981,0.00001540949,0.0001516634,0.00002133242,0.0000287551,0.0003879246],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002897515,"threshold_uncertainty_score":0.009809852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06653002476833615,"score_gpt":0.433900862143319,"score_spread":0.3673708373749828,"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."}}