{"id":"W2785171343","doi":"10.1007/s12193-018-0260-8","title":"Use of tactons to communicate a risk level through an enactive shoe","year":2018,"lang":"en","type":"article","venue":"Journal on Multimodal User Interfaces","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Set (abstract data type); Repetition (rhetorical device); Channel (broadcasting); Haptic technology; Human–computer interaction; Speech recognition; Artificial intelligence; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001105881,0.0002460004,0.0003162143,0.0002170798,0.000492081,0.0002566201,0.0007080788,0.0000937213,0.0004678878],"category_scores_gemma":[0.001220121,0.0001915231,0.0001461453,0.000244914,0.0002321014,0.002233544,0.0001475235,0.0009592907,0.000419291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001187373,"about_ca_system_score_gemma":0.00004884661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000909944,"about_ca_topic_score_gemma":0.0004486969,"domain_scores_codex":[0.9978582,0.0005504609,0.0005183757,0.0003472158,0.0003723074,0.0003534037],"domain_scores_gemma":[0.9974281,0.0009534083,0.0004783122,0.0006374356,0.0002726263,0.0002301834],"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":[0.001214924,0.0008474293,0.001292245,0.00000313799,0.00006535018,0.00002227594,0.01144759,0.001102515,0.9783092,0.0002545264,0.002056139,0.003384642],"study_design_scores_gemma":[0.000386722,0.001866433,0.004820603,0.0001015197,0.00002977054,0.0001185569,0.0009881228,0.001577837,0.9427826,0.0001248949,0.04697651,0.000226426],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951118,0.000002611424,0.001292239,0.0007339726,0.0008621344,0.0001974235,0.0002320729,0.00004616681,0.001521626],"genre_scores_gemma":[0.9931843,0.0001010719,0.004366221,0.001368659,0.0001878475,0.000005726832,7.575379e-7,0.00003485904,0.0007505429],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04492037,"threshold_uncertainty_score":0.7810087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2674031292362047,"score_gpt":0.3977811575371967,"score_spread":0.130378028300992,"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."}}