{"id":"W3129382303","doi":"10.1002/aisy.202000229","title":"Human–Machine Collaboration for Automated Driving Using an Intelligent Two‐Phase Haptic Interface","year":2021,"lang":"en","type":"article","venue":"Advanced Intelligent Systems","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"State Key Laboratory of Automotive Safety and Energy; National Natural Science Foundation of China; Nanyang Technological University","keywords":"Haptic technology; Human–machine system; Computer science; Interface (matter); Human–computer interaction; Control (management); Smoothness; Torque; Driving simulator; Human–machine interface; Automation; Steering wheel; Simulation; Engineering; Artificial intelligence; Automotive 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":[0.0003814161,0.0003226023,0.0002058574,0.00016636,0.0002061314,0.0004202786,0.0005270118,0.0005633211,0.0015854],"category_scores_gemma":[0.0007367356,0.0001473245,0.0002765898,0.00008723997,0.000285186,0.0005891189,0.0007394525,0.0003408918,0.0002596737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001280399,"about_ca_system_score_gemma":0.0003068916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004089748,"about_ca_topic_score_gemma":0.0005322499,"domain_scores_codex":[0.9997607,0.00008071736,0.0000112546,0.0000380256,0.00008878657,0.00002053097],"domain_scores_gemma":[0.9997781,0.0001022506,0.00002333873,0.00003599643,0.00004082666,0.00001942906],"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":[0.0007520714,0.000917478,0.003195275,0.0004519119,0.0001305552,0.000750141,0.001462109,0.1318887,0.4779882,0.02265707,0.002997618,0.3568089],"study_design_scores_gemma":[0.00005892502,0.0007856613,0.001432579,0.00001683218,0.00003066287,0.0003132244,0.00009456725,0.9739884,0.01558293,0.003201278,0.004459426,0.00003551149],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04245647,0.0001013357,0.9547968,0.00009193562,0.00004445733,0.00007027028,0.000009670012,0.0004222969,0.002006687],"genre_scores_gemma":[0.874203,0.00009159889,0.1238386,0.00005785776,0.00002359784,0.000104334,0.00001970199,0.00001630825,0.001644981],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0015854,"threshold_uncertainty_score":0.005303681,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06437668381603019,"score_gpt":0.4604792289181868,"score_spread":0.3961025451021566,"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."}}