{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0175248,0.0004693739,0.001150185,0.003349332,0.001712188,0.0002952466,0.0012604,0.000469255,0.0007962031],"category_scores_gemma":[0.000921238,0.000490427,0.0005050167,0.01188909,0.001931416,0.001511873,0.00002246691,0.001690953,0.00004631933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004620271,"about_ca_system_score_gemma":0.001987978,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6376933,"about_ca_topic_score_gemma":0.7480485,"domain_scores_codex":[0.9817091,0.004194927,0.002142163,0.001582396,0.008406661,0.001964752],"domain_scores_gemma":[0.9861681,0.001949757,0.000444681,0.001058213,0.008819217,0.001559993],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005784133,0.001520197,0.826088,0.00005625945,0.0006793424,0.003061703,0.1651565,0.000634548,0.0001461938,0.0003424556,0.0006930684,0.001043307],"study_design_scores_gemma":[0.001536696,0.0004665491,0.7219325,0.00005226596,0.0008567374,2.099488e-7,0.2725838,0.0004246777,0.0001307652,0.0002564662,0.001375463,0.0003839293],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921715,0.0002446086,0.0002028635,0.0003068837,0.0002308886,0.003255422,0.001539481,0.0006823473,0.001365992],"genre_scores_gemma":[0.9965919,0.00005958105,0.0009937969,0.00002146837,0.0001964767,0.0006017874,0.001079867,0.000075821,0.0003792598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1103553,"threshold_uncertainty_score":0.9997547,"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."}}