{"id":"W6926081455","doi":"10.21227/5hyq-sw82","title":"IoT Time-Series Traffic Data: Smart City, eHealth, and Smart Factory","year":2024,"lang":"en","type":"dataset","venue":"IEEE DataPort","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Slicing; Internet of Things; Enhanced Data Rates for GSM Evolution; Resource (disambiguation); Transmission (telecommunications); Resource allocation; Volume (thermodynamics); Factory (object-oriented programming)","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":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","insufficient_payload"],"category_scores_codex":[0.00241649,0.001636698,0.001864417,0.0009652458,0.0003953592,0.0007891672,0.004181541,0.001124193,0.002477928],"category_scores_gemma":[0.0002992628,0.001631946,0.0001691795,0.0008095027,0.0009456124,0.001412057,0.002906113,0.002653953,0.1402129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003311101,"about_ca_system_score_gemma":0.001779601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001489579,"about_ca_topic_score_gemma":0.007739807,"domain_scores_codex":[0.9913619,0.000292823,0.001573812,0.003587049,0.001700278,0.001484165],"domain_scores_gemma":[0.9887016,0.0002460358,0.0007071318,0.009353975,0.000138769,0.000852472],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001288765,0.0002181409,0.00006171337,0.001562374,0.0004918241,0.001117506,0.00002932376,0.000003199983,0.00004774375,9.490453e-7,0.9959266,0.0004117467],"study_design_scores_gemma":[0.0004314331,0.0001636882,0.0002678053,0.000442904,0.001095823,0.0006521544,0.00002639558,0.00004872079,0.00002616497,0.00001724279,0.9952731,0.001554624],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001311783,0.00171574,0.000001401901,0.000145171,0.00513469,0.00117626,0.9895323,0.0007949154,0.0001877703],"genre_scores_gemma":[0.00002947428,0.001128721,0.0001606372,0.0003497886,0.001705412,0.00008717199,0.9937156,0.0004556094,0.002367627],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1377349,"threshold_uncertainty_score":0.999647,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05575840687551047,"score_gpt":0.3183058338640365,"score_spread":0.2625474269885261,"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."}}