{"id":"W4410719414","doi":"10.59075/67asf781","title":"Optimizing Convolutional Neural Networks for Real-Time Object Detection in Autonomous Vehicles","year":2025,"lang":"en","type":"article","venue":"The critical review of social sciences studies","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Convolutional neural network; Computer science; Artificial intelligence; Object (grammar); Object detection; Computer vision; Real-time computing; Pattern recognition (psychology)","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":[0.001040131,0.0001235319,0.0003514755,0.00005404986,0.0009324668,0.00003858151,0.0006870618,0.00003687928,0.000001394497],"category_scores_gemma":[0.000447615,0.0000902861,0.0001249399,0.001327946,0.001174186,0.0002314474,0.0002955951,0.0001236825,0.000001435206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001091043,"about_ca_system_score_gemma":0.00007768784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001366666,"about_ca_topic_score_gemma":0.0000364443,"domain_scores_codex":[0.9985018,0.0001423052,0.0004348033,0.0003572732,0.0002052935,0.000358464],"domain_scores_gemma":[0.9974016,0.002100453,0.0000996701,0.0001524295,0.0002213487,0.0000244887],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008646767,0.00007431959,0.0000702094,0.0009026253,0.00003408206,6.314902e-7,0.0003875381,0.002250105,0.0004624493,0.829556,0.001152403,0.1651009],"study_design_scores_gemma":[0.0003338396,0.0001934928,0.001610198,0.001717406,0.000082001,0.000003346958,0.0002885042,0.8421699,0.0001426991,0.1481282,0.004961412,0.000368998],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001231252,0.1245867,0.8325436,0.03552627,0.0007953396,0.001917881,0.000009712991,0.0002010673,0.003188214],"genre_scores_gemma":[0.9625595,0.01414379,0.02036886,0.002130162,0.0001809802,0.000542901,0.000001172311,0.00000617299,0.00006643692],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9613283,"threshold_uncertainty_score":0.7171875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04707215235764465,"score_gpt":0.3707086584022605,"score_spread":0.3236365060446158,"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."}}