{"id":"W3190659906","doi":"10.1016/j.jksuci.2021.07.020","title":"Intelligent transportation systems: A survey on modern hardware devices for the era of machine learning","year":2021,"lang":"en","type":"article","venue":"Journal of King Saud University - Computer and Information Sciences","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Software deployment; Bridging (networking); Task (project management); Variety (cybernetics); Field (mathematics); Software; Machine learning; Data science; Artificial intelligence; Risk analysis (engineering); Embedded system; Human–computer interaction; Software engineering; Computer security; Systems engineering; Operating system","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":[0.0003991252,0.00003530571,0.00007000096,0.0001019864,0.0001094306,0.00005860381,0.00009197462,0.00001419222,9.307745e-7],"category_scores_gemma":[0.000008045079,0.00002663289,0.00002877349,0.0001317391,0.00002316707,0.000783099,0.000006706281,0.00007418961,9.674017e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001481084,"about_ca_system_score_gemma":0.00001656665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002875914,"about_ca_topic_score_gemma":0.00004389746,"domain_scores_codex":[0.9996246,0.0000202171,0.0001565333,0.00002541796,0.0001326619,0.00004058928],"domain_scores_gemma":[0.9996205,0.00009219859,0.0001136023,0.00002337936,0.0001343292,0.00001598529],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001855597,0.000007573839,0.00260898,0.00009862681,0.0000463393,8.262896e-7,0.002282902,0.8805946,0.00001048125,0.001700047,0.0008093084,0.1118218],"study_design_scores_gemma":[0.0001350167,0.00008741354,0.03661103,0.0001019709,0.00001341584,0.000003081622,0.0007895444,0.9438605,0.00006522302,0.000006374431,0.01829203,0.00003445203],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04151459,0.0001367072,0.9578139,0.00008679548,0.0002121771,0.0000503783,0.00001214919,0.00004707721,0.0001262941],"genre_scores_gemma":[0.9979239,0.000492677,0.001526174,0.00003358207,0.00001230681,6.594015e-8,0.000006741727,8.476277e-7,0.000003757823],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9564093,"threshold_uncertainty_score":0.1086058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01833997870677184,"score_gpt":0.2143487099299463,"score_spread":0.1960087312231745,"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."}}