{"id":"W1971906315","doi":"10.1109/haptics.2014.6775476","title":"Improvising design with a Haptic Instrument","year":2014,"lang":"en","type":"article","venue":"","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Haptic technology; Tweaking; Computer science; Human–computer interaction; Visualization; Improvisation; Stereotaxy; Multimedia; Simulation; Artificial intelligence","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":[0.00002081495,0.00005968917,0.00005296307,0.00003773917,0.0001041553,0.00005864909,0.00006347823,0.0000139113,0.0001637435],"category_scores_gemma":[0.00009468379,0.00004047479,0.00001526977,0.00007178893,0.00002692664,0.0001599356,0.00001034823,0.00006855811,0.000236106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001591962,"about_ca_system_score_gemma":0.00001328308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002511244,"about_ca_topic_score_gemma":0.000007445467,"domain_scores_codex":[0.9994918,0.00004905972,0.00006741683,0.0001649168,0.00009785179,0.0001289601],"domain_scores_gemma":[0.9996037,0.0001730898,0.00002574631,0.000142068,0.00000998683,0.00004535226],"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":[0.00003506037,0.00004063341,0.00004464766,0.000002262115,0.000001918095,0.000004816131,0.000147545,0.000159714,0.9782877,0.004817328,0.0001623844,0.01629599],"study_design_scores_gemma":[0.0002209074,0.0002969784,0.00005728358,0.000008112222,0.000005735606,0.00008064249,0.00007775666,0.0240516,0.9677953,0.0002602248,0.007046824,0.00009864748],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5707809,3.101412e-7,0.3225566,0.0006153272,0.0002126946,0.0001953241,5.203373e-7,0.0001944657,0.1054439],"genre_scores_gemma":[0.9937496,6.916162e-7,0.002705407,0.001112466,0.0000277283,0.000006145553,7.064984e-8,0.000007421785,0.002390438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4229688,"threshold_uncertainty_score":0.3034744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05476626320525826,"score_gpt":0.2609104538151811,"score_spread":0.2061441906099228,"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."}}