{"id":"W103335820","doi":"","title":"Automated Analysis of Walking Behavior: A Case Study from Qatar","year":2015,"lang":"en","type":"article","venue":"Transportation Research Board 94th Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pedestrian; Distraction; Data collection; Gait analysis; Gait; Preferred walking speed; Transport engineering; Computer science; Psychology; Physical medicine and rehabilitation; Engineering; Medicine; Cognitive psychology; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007511785,0.0003798221,0.0003155317,0.00103061,0.001302862,0.0005328117,0.0005625029,0.0009892196,0.0008538024],"category_scores_gemma":[0.001681012,0.0001710725,0.0004016841,0.001303098,0.0005386303,0.0003109625,0.0005021474,0.0004369013,0.0003197616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008246074,"about_ca_system_score_gemma":0.0006826161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03600144,"about_ca_topic_score_gemma":0.07984482,"domain_scores_codex":[0.9994984,0.0001812922,0.00004033934,0.00008863258,0.0001032607,0.00008803295],"domain_scores_gemma":[0.9989753,0.000445939,0.0001223144,0.00009710603,0.0002743468,0.00008504007],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007052069,0.003559869,0.6201387,0.0007822792,0.0002227422,0.08400151,0.08602459,0.01360744,0.02718055,0.001810181,0.006593747,0.1553732],"study_design_scores_gemma":[0.00005966668,0.001555285,0.8666579,0.0001495013,0.0001435455,0.01112411,0.06478252,0.0396349,0.006826787,0.000934812,0.008040465,0.00009046292],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972708,0.00003609481,0.001618114,0.0001403716,0.000005204242,0.00007201919,0.0002537528,0.00002139532,0.0005822845],"genre_scores_gemma":[0.9909931,0.0001315349,0.007212694,0.00008233416,0.00001169768,0.00004822515,0.0004187381,0.00001345228,0.001088314],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03600144,"threshold_uncertainty_score":0.07158381,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1405473562681029,"score_gpt":0.4679435804413482,"score_spread":0.3273962241732453,"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."}}