{"id":"W2116347609","doi":"10.1109/tai.1995.479843","title":"An artificial neural network for the design of an adaptive multimodal interface","year":2002,"lang":"en","type":"article","venue":"","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Innovation, Science and Economic Development Canada","funders":"","keywords":"Computer science; Interface (matter); Artificial neural network; Protocol (science); Human–computer interaction; Conceptual design; User interface; Basis (linear algebra); Artificial intelligence; 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":[0.0009434246,0.0006405166,0.0003608552,0.0004044102,0.0004049796,0.000682127,0.0007723917,0.001038565,0.002392654],"category_scores_gemma":[0.001839947,0.0003211076,0.0004053365,0.0003425399,0.0003820192,0.0006789775,0.0004204453,0.0008579003,0.0005504765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004927741,"about_ca_system_score_gemma":0.0005767426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002669938,"about_ca_topic_score_gemma":0.004086664,"domain_scores_codex":[0.9996867,0.00009869267,0.00002440354,0.0000565966,0.0001144726,0.00001905985],"domain_scores_gemma":[0.9997182,0.0001206695,0.00002232366,0.00001434645,0.0001157411,0.000008743774],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001488115,0.00006151298,0.0007881136,0.0002939169,0.00008562642,0.0002288368,0.0001596137,0.7001809,0.02009593,0.02192974,0.001908903,0.2541181],"study_design_scores_gemma":[0.00000982158,0.00004288066,0.000113759,0.00003024131,0.00002080627,0.00004171169,0.00001085738,0.9908346,0.00283999,0.002223159,0.003823123,0.000008999663],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003492211,0.0002593658,0.9931096,0.0001001869,0.0000417535,0.00006170615,0.00001514336,0.0002682649,0.002651813],"genre_scores_gemma":[0.2253957,0.0007086382,0.7672931,0.0001570328,0.00005393367,0.0006673294,0.00007755798,0.00006611823,0.005580573],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002669938,"threshold_uncertainty_score":0.008004189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1590231244261945,"score_gpt":0.3314502186327767,"score_spread":0.1724270942065822,"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."}}