{"id":"W2177079828","doi":"10.1109/whc.2005.86","title":"Learning and Identifying Haptic Icons under Workload","year":2005,"lang":"en","type":"article","venue":"","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":93,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Haptic technology; Workload; Intrusiveness; Computer science; Task (project management); Set (abstract data type); Human–computer interaction; Variable (mathematics); Task analysis; Work (physics); Multimedia; Artificial intelligence; Psychology; Engineering","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":[0.0006669813,0.0005340936,0.000394753,0.0002275785,0.000157155,0.0007097939,0.0004996224,0.0004406552,0.00151244],"category_scores_gemma":[0.01005732,0.0001857283,0.0001630526,0.00009787468,0.0003970051,0.0008977515,0.0007216188,0.0004534778,0.0002654274],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001554461,"about_ca_system_score_gemma":0.0002063721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003116469,"about_ca_topic_score_gemma":0.0004111038,"domain_scores_codex":[0.9993845,0.0001324252,0.00003753171,0.0001404152,0.000202739,0.0001022862],"domain_scores_gemma":[0.9968284,0.001947188,0.0004769329,0.0002947452,0.0002584639,0.0001941729],"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":[0.001230997,0.0004132083,0.006232703,0.0001663998,0.00001853677,0.0001326744,0.0007769891,0.003145003,0.8992845,0.0001898715,0.0001044363,0.08830464],"study_design_scores_gemma":[0.0001384344,0.01431212,0.1094972,0.00006831258,0.0001123099,0.001135668,0.001331778,0.04246541,0.8273255,0.001323023,0.002167967,0.000122309],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911259,0.00003836444,0.008306127,0.00001745864,0.000009008887,0.00002910505,0.000007240336,0.00003278015,0.0004340897],"genre_scores_gemma":[0.9901661,0.00009393979,0.008524627,0.00003965114,0.00001805165,0.00003354936,0.00004231938,0.00002294151,0.001058924],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00151244,"threshold_uncertainty_score":0.0050596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06598491380645687,"score_gpt":0.329310350293389,"score_spread":0.2633254364869321,"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."}}