{"id":"W3034703645","doi":"10.1155/2020/3828395","title":"Traffic State Recognition of Intersection Based on Image Model and PCA Hashing","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"North China University of Technology; Beijing Municipal Education Commission","keywords":"Intersection (aeronautics); Computer science; Intelligent transportation system; Feature extraction; Artificial intelligence; Traffic flow (computer networking); Field (mathematics); Feature (linguistics); Data mining; Pattern recognition (psychology); Computer vision; Engineering; Computer network","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002173572,0.0004714028,0.0004671603,0.0007767347,0.0003290868,0.0007792951,0.0006250553,0.000504453,0.0009943836],"category_scores_gemma":[0.0006314541,0.0002628386,0.0006888374,0.0007853306,0.0004896487,0.001743228,0.0005904374,0.0005538287,0.0005688334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003514657,"about_ca_system_score_gemma":0.0005889702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00303279,"about_ca_topic_score_gemma":0.001660668,"domain_scores_codex":[0.9995938,0.00003696829,0.00001552192,0.000131205,0.0001728717,0.00004962165],"domain_scores_gemma":[0.9998363,0.00002190487,0.00002245405,0.00004070214,0.00006777266,0.00001077654],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003328064,0.0001696013,0.008434055,0.0001755077,0.00009843713,0.0002463835,0.0003836788,0.1562514,0.1106679,0.02125117,0.00385131,0.6981378],"study_design_scores_gemma":[0.000009381322,0.0000928379,0.003248995,0.000006566298,0.00002678936,0.0002912133,0.00006347088,0.9729043,0.01911438,0.002525767,0.001673519,0.00004275501],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04841095,0.0001443664,0.9485331,0.00008380598,0.00004353813,0.00005226041,0.00008240109,0.0007228804,0.00192661],"genre_scores_gemma":[0.7944139,0.0004489065,0.2009654,0.00005908358,0.00005969982,0.0001162292,0.0004532258,0.00006573836,0.003417823],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00303279,"threshold_uncertainty_score":0.006030321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02967093885505266,"score_gpt":0.2787021295791527,"score_spread":0.2490311907241,"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."}}