{"id":"W2294484138","doi":"10.1145/2818346.2820756","title":"Different Strokes and Different Folks","year":2015,"lang":"en","type":"article","venue":"","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Gesture; Context (archaeology); Computer science; Robot; Human–computer interaction; Computer vision; Haptic technology; Cover (algebra); Object (grammar); Gesture recognition; Artificial intelligence; Channel (broadcasting); Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003426229,0.0004047658,0.0003890907,0.0006938596,0.001178827,0.00250252,0.0003692824,0.0006892564,0.01804683],"category_scores_gemma":[0.0030798,0.000149564,0.0002693921,0.0008231358,0.002556445,0.003178453,0.001308362,0.0009219605,0.003379827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002524759,"about_ca_system_score_gemma":0.0001620946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004924637,"about_ca_topic_score_gemma":0.001521935,"domain_scores_codex":[0.9995577,0.00009175009,0.00002884411,0.0001156425,0.0001408605,0.00006518266],"domain_scores_gemma":[0.9993193,0.0002539542,0.00005864585,0.00017171,0.000103527,0.00009290671],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001148646,0.0001405338,0.02248073,0.001707262,0.000235206,0.002816596,0.05352646,0.0008923188,0.08121884,0.1547688,0.04649637,0.6345682],"study_design_scores_gemma":[0.00005231124,0.0005729715,0.08171621,0.0007796363,0.0001185323,0.006289898,0.03958878,0.003212734,0.01914701,0.07339013,0.774875,0.0002567775],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5288107,0.005529535,0.0627608,0.003907018,0.002732218,0.0001398846,0.001149662,0.001493077,0.3934771],"genre_scores_gemma":[0.8916267,0.001432877,0.02133242,0.002030291,0.0002878628,0.00006837746,0.0003289755,0.0005216183,0.08237084],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01804683,"threshold_uncertainty_score":0.06037265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09014515592219298,"score_gpt":0.3016161568420997,"score_spread":0.2114710009199068,"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."}}