{"id":"W4410749204","doi":"10.1155/atr/2728315","title":"Research on Machine Vision–Based Intelligent Tracking System for Maintenance Personnel","year":2025,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China","keywords":"Tracking (education); Computer science; Machine vision; Tracking system; Systems engineering; Engineering; Artificial intelligence; Psychology; Kalman filter","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002787729,0.0001285465,0.0002839416,0.0005306465,0.000211436,0.00008278689,0.0005100419,0.00006161335,0.000001126668],"category_scores_gemma":[0.0001377146,0.0001054021,0.0002009654,0.0007365557,0.00003380399,0.0004759799,0.000003788178,0.0003563669,0.000001526345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001721218,"about_ca_system_score_gemma":0.0001598934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003565513,"about_ca_topic_score_gemma":0.00002867506,"domain_scores_codex":[0.998167,0.0001749859,0.0006193027,0.0002625461,0.0004964292,0.00027971],"domain_scores_gemma":[0.9974779,0.0009037424,0.0003112305,0.0002626897,0.000975299,0.00006916965],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001633916,0.0003842006,0.001258659,0.0008631654,0.0001082333,0.0001376492,0.00245798,0.3714211,0.008714756,0.123116,0.0002489515,0.4896554],"study_design_scores_gemma":[0.02283007,0.00952413,0.3560678,0.01943166,0.0002229573,0.00008199014,0.01605656,0.2000257,0.2927836,0.03896162,0.0421979,0.001815978],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04280181,0.0003254043,0.9540548,0.001300847,0.001092192,0.0002556066,0.000007255626,0.0000400842,0.0001219824],"genre_scores_gemma":[0.8508081,0.00003287212,0.1489153,0.000119685,0.0000602812,0.00001275706,0.0000040189,0.000009423307,0.00003756006],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8080063,"threshold_uncertainty_score":0.4298174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04913162442548397,"score_gpt":0.3945590376057466,"score_spread":0.3454274131802626,"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."}}