{"id":"W4403920087","doi":"10.1109/sm63044.2024.10733535","title":"Robot Wheelchair Convoys for Assistive Human Transportation","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; York University","funders":"","keywords":"Wheelchair; Robot; Computer science; Human–computer interaction; Human–robot interaction; Artificial intelligence; World Wide Web","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":[0.000163497,0.0005792632,0.0002946081,0.0002000316,0.0004275055,0.0004144706,0.0007381756,0.0003793394,0.003837788],"category_scores_gemma":[0.000255723,0.0001544411,0.0002350677,0.0001244636,0.0002915151,0.0004042762,0.0008157149,0.0002484095,0.001045767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002071048,"about_ca_system_score_gemma":0.0004965045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005744671,"about_ca_topic_score_gemma":0.007429217,"domain_scores_codex":[0.9998488,0.00004039557,0.000007455587,0.00003387953,0.0000451475,0.00002422469],"domain_scores_gemma":[0.9998869,0.00001522854,0.00001006778,0.00002112816,0.00004070731,0.00002598558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00174998,0.0004084394,0.004088258,0.001033447,0.0001643406,0.001928049,0.001274556,0.05323225,0.3631505,0.01479608,0.01884494,0.5393292],"study_design_scores_gemma":[0.0003114795,0.003381778,0.01307604,0.0002326275,0.000228585,0.002524839,0.001019089,0.5865569,0.120633,0.008563424,0.2633002,0.0001720092],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2044744,0.002005889,0.7669617,0.0004123701,0.0003031839,0.0003435399,0.0003520595,0.007901522,0.01724526],"genre_scores_gemma":[0.8981011,0.0005307193,0.08895793,0.00009000695,0.0000358137,0.0001704725,0.0004439056,0.00009842529,0.01157171],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005744671,"threshold_uncertainty_score":0.01283872,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01772039263657451,"score_gpt":0.2691380128359439,"score_spread":0.2514176201993694,"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."}}