{"id":"W3121355958","doi":"10.4271/2021-01-0175","title":"Infrastructure-Based Sensor Data Capture Systems for Measurement of Operational Safety Assessment (OSA) Metrics","year":2021,"lang":"en","type":"article","venue":"SAE International Journal of Advances and Current Practices in Mobility","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Transport Canada","funders":"","keywords":"Intersection (aeronautics); Computer science; Intelligent transportation system; Real-time computing; Lidar; Ranging; Transport engineering; Simulation; Engineering; Telecommunications; Remote sensing","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":[0.0006545285,0.000519706,0.0002961171,0.00112281,0.0002993434,0.0007764398,0.0008542747,0.0004582039,0.007164657],"category_scores_gemma":[0.001550514,0.0002241469,0.0001787157,0.0009610069,0.0002156764,0.0008328215,0.0005295862,0.0005424897,0.001938076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007930868,"about_ca_system_score_gemma":0.0006630835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001484829,"about_ca_topic_score_gemma":0.00247272,"domain_scores_codex":[0.9989887,0.0001678599,0.00005786633,0.0001804906,0.0005521362,0.00005292832],"domain_scores_gemma":[0.9987344,0.0002423606,0.0001610019,0.0001967034,0.0006219781,0.00004364154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004527381,0.000435848,0.01737995,0.0007371462,0.0001109065,0.0002243348,0.0005028066,0.0201966,0.4853035,0.0118482,0.02756855,0.4352395],"study_design_scores_gemma":[0.0001097958,0.001551768,0.05101365,0.0002680045,0.0001378493,0.0006920269,0.0004262197,0.2411731,0.6006867,0.003868714,0.099876,0.0001962031],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06258139,0.0003444996,0.9066241,0.0003019916,0.0002120064,0.001117037,0.003447194,0.00813979,0.01723205],"genre_scores_gemma":[0.5551939,0.000448602,0.4278179,0.000465774,0.0001218022,0.001438942,0.003083399,0.0003628491,0.01106693],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007164657,"threshold_uncertainty_score":0.02396816,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04440900978509965,"score_gpt":0.360190049119274,"score_spread":0.3157810393341744,"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."}}