{"id":"W2333266351","doi":"10.1177/154193120104502310","title":"Detection of Cars and Pedestrians While Making Left Turn Decisions","year":2001,"lang":"en","type":"article","venue":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","topic":"Traffic and Road Safety","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Change blindness; Pedestrian; Intersection (aeronautics); Blindness; Psychology; Transport engineering; Computer science; Change detection; Engineering; Artificial intelligence; Medicine; Optometry","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":[0.001028789,0.0002838907,0.0004180687,0.0006549584,0.0003232062,0.001192129,0.0002308153,0.0006439817,0.00190834],"category_scores_gemma":[0.01461459,0.0004926193,0.0002525874,0.0001809891,0.0003724717,0.001077487,0.0006890798,0.0005671575,0.0004421881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003202693,"about_ca_system_score_gemma":0.000591566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00602702,"about_ca_topic_score_gemma":0.005292922,"domain_scores_codex":[0.9990847,0.0002380824,0.00004643021,0.0001873044,0.0002726139,0.0001708847],"domain_scores_gemma":[0.9943569,0.002743574,0.001448535,0.0002419816,0.0006773888,0.0005314969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.008471232,0.001156611,0.6754236,0.000348495,0.0002318327,0.0006700909,0.0118849,0.00158354,0.1927905,0.0005507092,0.001059726,0.1058287],"study_design_scores_gemma":[0.00009404498,0.002166924,0.9580571,0.00004972543,0.0001292402,0.0007378434,0.00317611,0.00951633,0.0229221,0.001095734,0.00192831,0.0001264633],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997897,0.0001057546,0.001138437,0.00004414437,0.00001038527,0.00001930118,0.00003722202,0.00002856858,0.0007191116],"genre_scores_gemma":[0.9980349,0.00006157598,0.001215677,0.00005560348,0.000005712604,0.00001288801,0.00006443513,0.00001096354,0.0005382214],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00602702,"threshold_uncertainty_score":0.01198387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01577019593429203,"score_gpt":0.2134722804625618,"score_spread":0.1977020845282698,"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."}}