{"id":"W2592496287","doi":"10.1109/ivs.2017.7995730","title":"Agreeing to cross: How drivers and pedestrians communicate","year":2017,"lang":"en","type":"article","venue":"","topic":"Traffic and Road Safety","field":"Engineering","cited_by":227,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Schema crosswalk; Pedestrian crossing; Pedestrian; Computer science; Collision; Gaze; Point (geometry); Event (particle physics); Transport engineering; Human–computer interaction; Computer security; Artificial intelligence; Engineering; Mathematics","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":[0.0007528049,0.0004294583,0.0002969945,0.001112094,0.0004296461,0.001364826,0.0004080528,0.0008713814,0.002015736],"category_scores_gemma":[0.005378078,0.000190948,0.0002860045,0.000871315,0.0003281338,0.001732667,0.0009703079,0.0005735658,0.001014097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003825584,"about_ca_system_score_gemma":0.0002423844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006904453,"about_ca_topic_score_gemma":0.00656406,"domain_scores_codex":[0.999028,0.0004214781,0.0000481809,0.000259652,0.000124326,0.0001183803],"domain_scores_gemma":[0.9970702,0.001683623,0.000496286,0.0002163625,0.0002986733,0.0002348144],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00123354,0.0003249446,0.8772156,0.0005277023,0.0003004344,0.000686612,0.01641934,0.001673564,0.006684478,0.001597752,0.01536318,0.07797289],"study_design_scores_gemma":[0.00003261796,0.0002777814,0.9302616,0.0001041278,0.0001896087,0.001107482,0.01963811,0.01562166,0.002891044,0.003623993,0.02614517,0.0001068408],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9875651,0.0008377627,0.002311884,0.0005059248,0.00005179237,0.00002946748,0.00416236,0.00008331094,0.004452333],"genre_scores_gemma":[0.9929383,0.0002579345,0.000863929,0.00009664272,0.00004538763,0.0000218867,0.00491579,0.00001685782,0.0008432069],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006904453,"threshold_uncertainty_score":0.01372856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01870081798629786,"score_gpt":0.2483561671291605,"score_spread":0.2296553491428626,"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."}}