{"id":"W4296195610","doi":"10.1007/978-3-031-04043-6_2","title":"User Experience and Mid-Air Haptics: Applications, Methods, and Challenges","year":2022,"lang":"en","type":"book-chapter","venue":"Human-computer interaction series","topic":"Tactile and Sensory Interactions","field":"Neuroscience","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"European Commission","keywords":"Haptic technology; Perspective (graphical); Implementation; Computer science; Human–computer interaction; User experience design; Multimedia; Quality (philosophy); Simulation; Software engineering; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0000763846,0.0004915672,0.0004711038,0.0003579412,0.0008239025,0.00025268,0.0002874468,0.0001869485,0.001765475],"category_scores_gemma":[0.00002846914,0.0005230707,0.0001277251,0.00004027639,0.0003347087,0.00125233,0.0004265339,0.0008097861,0.00007923262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009821152,"about_ca_system_score_gemma":0.00002095965,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001779558,"about_ca_topic_score_gemma":0.00002705289,"domain_scores_codex":[0.997655,0.0001434668,0.0005314001,0.001121876,0.0002902377,0.0002580446],"domain_scores_gemma":[0.9982689,0.0005119792,0.0004167696,0.0005873493,0.00007876578,0.0001362552],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001873291,0.0001581075,0.000008970441,0.0004453282,0.0001568448,0.0001077147,0.01131264,0.0000335168,0.03852402,0.7895263,0.002895656,0.1566436],"study_design_scores_gemma":[0.0001419332,0.0001695306,0.00003776647,0.00006232776,0.00004263101,0.0008101912,0.0006926055,0.00004782161,0.01184195,0.003562118,0.9821095,0.0004816365],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.01125983,0.005660827,0.01444207,0.007984854,0.01221824,0.004427823,0.0004219463,0.002351184,0.9412332],"genre_scores_gemma":[0.06209652,0.05858023,0.02343881,0.005111972,0.003713005,0.001746193,0.0001386255,0.0005765429,0.8445981],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9792138,"threshold_uncertainty_score":0.9997221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1263384325260957,"score_gpt":0.3665461805549053,"score_spread":0.2402077480288096,"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."}}