{"id":"W1977247366","doi":"10.1109/jtehm.2014.2365773","title":"Automatic Detection and Classification of Unsafe Events During Power Wheelchair Use","year":2014,"lang":"en","type":"review","venue":"IEEE Journal of Translational Engineering in Health and Medicine","topic":"Gaze Tracking and Assistive Technology","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; Université Laval; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Fonds Québécois de la Recherche sur la Nature et les Technologies","keywords":"Wheelchair; Computer science; Wavelet; Task (project management); Data mining; Artificial intelligence; Pattern recognition (psychology); Real-time computing; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003823467,0.000471412,0.0003862011,0.002118271,0.0001593345,0.0005711834,0.0003802353,0.0004884765,0.0005111025],"category_scores_gemma":[0.002864496,0.0001133009,0.0002501772,0.0008141564,0.0001341919,0.0004533566,0.0004069582,0.0002491917,0.0003886149],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001679806,"about_ca_system_score_gemma":0.000282518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003147526,"about_ca_topic_score_gemma":0.004186255,"domain_scores_codex":[0.9995447,0.00006296321,0.00005474999,0.00009560906,0.0001775982,0.00006451612],"domain_scores_gemma":[0.9986894,0.0004040762,0.0003290679,0.0001001936,0.0004040265,0.00007330274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001064089,0.000599617,0.4608686,0.0004062291,0.0001827262,0.0008553069,0.0006958332,0.01437537,0.07841792,0.0004252225,0.002503229,0.439606],"study_design_scores_gemma":[0.00001897316,0.0004433727,0.7318369,0.00008275606,0.00009248612,0.0007811614,0.0009641199,0.2380945,0.02504824,0.000528472,0.00205286,0.00005606865],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.9698971,0.0002020872,0.027771,0.00005729977,0.00003313405,0.0000679497,0.0007680199,0.0004304205,0.0007729761],"genre_scores_gemma":[0.9875544,0.0001334421,0.01077485,0.00001469908,0.00001710765,0.00003872795,0.0009956794,0.00001642862,0.0004546515],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.003147526,"threshold_uncertainty_score":0.006258368,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03932633372503046,"score_gpt":0.3181195564836848,"score_spread":0.2787932227586543,"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."}}