{"id":"W2949722557","doi":"10.48550/arxiv.1702.03555","title":"Agreeing to Cross: How Drivers and Pedestrians Communicate","year":2017,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Traffic and Road Safety","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Schema crosswalk; Pedestrian crossing; Pedestrian; Gaze; Collision; Computer science; Point (geometry); Transport engineering; Event (particle physics); Computer security; Artificial intelligence; Mathematics; 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":[0.0007099806,0.0004812819,0.0003158796,0.001222462,0.0004286879,0.001320775,0.0004289949,0.0009347582,0.002222179],"category_scores_gemma":[0.005114363,0.0001898616,0.0003085425,0.00101174,0.0003362523,0.001648057,0.0009787001,0.0006079861,0.001303027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004007345,"about_ca_system_score_gemma":0.0002373993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006995533,"about_ca_topic_score_gemma":0.00695842,"domain_scores_codex":[0.9990103,0.0004111364,0.00004644128,0.0002837059,0.0001250171,0.0001232891],"domain_scores_gemma":[0.9975554,0.001330508,0.0004296862,0.0002111337,0.0002649043,0.0002083027],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001402291,0.0003687186,0.8587191,0.0006164783,0.0003388296,0.0007535029,0.01385409,0.002083814,0.006852053,0.002027432,0.02436845,0.08861524],"study_design_scores_gemma":[0.0000368131,0.0002897295,0.9166028,0.0001177518,0.0001959973,0.001238906,0.01656117,0.01837822,0.003327098,0.0047974,0.03834328,0.0001107738],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9807809,0.001181139,0.003336999,0.0007412042,0.00007671397,0.00003697796,0.007812261,0.0001325539,0.005901362],"genre_scores_gemma":[0.9880434,0.0003251589,0.001234159,0.0001349932,0.00006305122,0.00002785402,0.008993641,0.00002365492,0.001154169],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006995533,"threshold_uncertainty_score":0.01390964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07788736856607857,"score_gpt":0.1884177169599148,"score_spread":0.1105303483938362,"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."}}