{"id":"W2744079410","doi":"10.1109/comst.2017.2736886","title":"Smart Cities: A Survey on Data Management, Security, and Enabling Technologies","year":2017,"lang":"en","type":"article","venue":"IEEE Communications Surveys & Tutorials","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":624,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Smart city; Interoperability; Computer security; Data management; Data security; Internet of Things; Data science; World Wide Web; Database","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":["sts","scholarly_communication","open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.01099741,0.0002324454,0.0003443481,0.0002245707,0.002184817,0.001634385,0.01445677,0.0001332147,7.709687e-7],"category_scores_gemma":[0.001677234,0.0002342435,0.00003734678,0.0002782387,0.0004809787,0.001059554,0.01115256,0.000333407,0.00004614945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004827843,"about_ca_system_score_gemma":0.00006646212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001680528,"about_ca_topic_score_gemma":0.0005515484,"domain_scores_codex":[0.9967119,0.001512517,0.0004443537,0.0006443842,0.0002890288,0.0003978319],"domain_scores_gemma":[0.9823326,0.001977102,0.0003850949,0.0150604,0.0001852892,0.00005951881],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000392152,0.0009607215,0.129809,0.0002339543,0.0007738824,0.00004677259,0.005258374,0.0000141996,0.0004467799,0.07224629,0.1609151,0.6292557],"study_design_scores_gemma":[0.002395455,0.0002177056,0.3834106,0.0007041071,0.00008928357,0.00002213756,0.000456487,0.02015993,0.001368242,0.05243555,0.5364938,0.00224665],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2961543,0.01120649,0.3362947,0.02472654,0.1970044,0.005913781,0.0005773032,0.01006728,0.1180552],"genre_scores_gemma":[0.9837887,0.002185019,0.01277215,0.00006584726,0.0006982757,0.00003230753,0.0001358194,0.00002564373,0.0002961808],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6876344,"threshold_uncertainty_score":0.999402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.179985358141876,"score_gpt":0.3629502118770322,"score_spread":0.1829648537351563,"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."}}