{"id":"W2771583656","doi":"10.1109/iccvw.2017.33","title":"Are They Going to Cross? A Benchmark Dataset and Baseline for Pedestrian Crosswalk Behavior","year":2017,"lang":"en","type":"article","venue":"","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":403,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Schema crosswalk; Pedestrian; Baseline (sea); Computer science; Benchmark (surveying); Minimum bounding box; Bounding overwatch; Point (geometry); Artificial intelligence; Machine learning; Pedestrian detection; Pedestrian crossing; Information retrieval; Human–computer interaction; Transport engineering; Image (mathematics); Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000265772,0.0001403218,0.0001682561,0.00004343475,0.0005148471,0.0001694326,0.0003111143,0.0001448574,0.0000666949],"category_scores_gemma":[0.0001828004,0.0001315809,0.00002947341,0.00001700398,0.00007589121,0.0001977806,0.0001352403,0.0001241604,0.00004035998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002188172,"about_ca_system_score_gemma":0.000008985487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004736347,"about_ca_topic_score_gemma":0.0009163178,"domain_scores_codex":[0.9992895,0.000004930353,0.0001707892,0.0002220729,0.0000460655,0.000266625],"domain_scores_gemma":[0.9991523,0.00005620062,0.00005386035,0.0006239548,0.00002231107,0.00009136253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002480682,0.0001898041,0.664253,0.0004118083,0.0001590527,0.0001542821,0.0004147128,0.002008686,0.007181454,0.002743016,0.08863082,0.2336053],"study_design_scores_gemma":[0.002067173,0.0001250788,0.7861639,0.00005903436,0.00008590028,0.00004167967,0.0001076754,0.02301064,0.006909359,0.000708431,0.1799139,0.0008072632],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9888474,0.0001007336,0.005667372,0.0005326644,0.0001801619,0.0005216519,0.002837839,0.0004105914,0.0009015448],"genre_scores_gemma":[0.9955004,0.00001635752,0.003647727,0.0001197188,0.00006078336,0.0001043615,0.0001861068,0.00002357256,0.0003410052],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2327981,"threshold_uncertainty_score":0.5365713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02574090554235806,"score_gpt":0.308778951740207,"score_spread":0.2830380461978489,"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."}}