{"id":"W2995786667","doi":"10.1109/comst.2019.2959013","title":"Cyber-Physical-Social Systems: A State-of-the-Art Survey, Challenges and Opportunities","year":2019,"lang":"en","type":"article","venue":"IEEE Communications Surveys & Tutorials","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":195,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Fundamental Research Funds for the Central Universities; China Postdoctoral Science Foundation; Natural Science Foundation of Shaanxi Province; National Natural Science Foundation of China","keywords":"Computer science; Virtualization; Architecture; Open research; Cyber-physical system; The Internet; Mobile computing; Mobile device; Internet of Things; Computer security; Data science; Telecommunications; World Wide Web; Cloud computing","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":[0.006388094,0.0002040246,0.0005064774,0.0001025452,0.000382396,0.0001807826,0.002731031,0.0000754128,6.069426e-7],"category_scores_gemma":[0.000185735,0.0001749588,0.00009982504,0.0002903417,0.0002771571,0.0003956885,0.001226005,0.0002269271,0.00004466079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005244374,"about_ca_system_score_gemma":0.0002058567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004500778,"about_ca_topic_score_gemma":0.0001020445,"domain_scores_codex":[0.9930068,0.005491294,0.0005226592,0.0003102829,0.0003633842,0.0003055312],"domain_scores_gemma":[0.9938317,0.002750701,0.0004107945,0.002491385,0.0004446961,0.00007074815],"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":[0.00005482951,0.002115503,0.01842162,0.001015151,0.001069767,0.000006529155,0.09380848,0.0002744395,0.007715422,0.218417,0.05131812,0.6057831],"study_design_scores_gemma":[0.002246183,0.000390442,0.5479971,0.0006529069,0.0000966135,0.00003178278,0.0006800469,0.02294072,0.001727497,0.01092426,0.4101152,0.00219716],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9010307,0.009711084,0.01047171,0.003954285,0.05700009,0.001739911,0.00005551483,0.0004547183,0.01558194],"genre_scores_gemma":[0.9968582,0.0009535342,0.000353643,0.00002879565,0.0007914919,0.00003009971,0.00001404932,0.00002122685,0.0009489986],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.603586,"threshold_uncertainty_score":0.7134613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.13638509768519,"score_gpt":0.3050766810040449,"score_spread":0.1686915833188549,"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."}}