{"id":"W4389290038","doi":"10.36227/techrxiv.24659457.v1","title":"Autonomic IoT Application Placement in Edge/Fog Computing","year":2023,"lang":"en","type":"preprint","venue":"","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Microservices; Cloud computing; Edge computing; Distributed computing; Fog computing; Energy consumption; Enhanced Data Rates for GSM Evolution; Computer network; Load balancing (electrical power); Edge device; Operating system; Engineering; Telecommunications","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007363465,0.0004460062,0.0006372915,0.000275429,0.000736325,0.0009782945,0.0008367698,0.0007338229,0.0006585609],"category_scores_gemma":[0.001314107,0.0003749037,0.0003716049,0.0004498808,0.0006805219,0.0009117984,0.001036006,0.0005541716,0.00009564182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00114331,"about_ca_system_score_gemma":0.001354478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005463621,"about_ca_topic_score_gemma":0.005500829,"domain_scores_codex":[0.999495,0.0001543418,0.00001689922,0.0001063942,0.0001024469,0.0001248319],"domain_scores_gemma":[0.9995871,0.0001615981,0.00006210673,0.0000524955,0.00005654931,0.00008006662],"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":[0.0001034734,0.00006871836,0.0008480913,0.00002846175,0.00002226189,0.0001231156,0.00006799256,0.9513654,0.004621933,0.02034678,0.0009677188,0.02143609],"study_design_scores_gemma":[0.000004388298,0.0000164882,0.0001759925,0.000002174417,0.000003630291,0.00001898172,0.00002253999,0.9938068,0.0005664487,0.005027437,0.0003521565,0.000003073909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1226828,0.0002324777,0.8696316,0.0002655385,0.00007289995,0.00007966317,0.00003288369,0.0001930884,0.006809012],"genre_scores_gemma":[0.9424768,0.0001385054,0.05568245,0.00007650525,0.0000212402,0.00003779,0.0000247033,0.00003171882,0.001510306],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005463621,"threshold_uncertainty_score":0.01086366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0378340493513195,"score_gpt":0.2868128179089586,"score_spread":0.2489787685576391,"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."}}