{"id":"W4291722496","doi":"10.1145/3524844.3528053","title":"Learning self-adaptations for IoT networks","year":2022,"lang":"en","type":"article","venue":"","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Adaptation (eye); Distributed computing; Flexibility (engineering); Context (archaeology); Network packet; Interoperability; Software-defined networking; Computer network","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":[0.0002484171,0.0000690821,0.00007737816,0.00004458276,0.0006939865,0.00008353125,0.0004314435,0.00001964781,0.0000865819],"category_scores_gemma":[0.0000175607,0.00006862931,0.00006122371,0.0003811929,0.000005465787,0.00007541158,0.0002491289,0.0001696617,0.000006946812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003457824,"about_ca_system_score_gemma":0.00005078951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001293046,"about_ca_topic_score_gemma":0.000005716929,"domain_scores_codex":[0.999233,0.00004747483,0.0001169523,0.0002293448,0.0001365012,0.0002367368],"domain_scores_gemma":[0.9993638,0.0003069203,0.00004394846,0.000201868,0.00003506355,0.00004833855],"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":[0.000003100863,0.00004169477,0.0007520035,0.00000162548,0.00001534262,0.000001973807,0.0004307519,0.7534198,0.000002238457,0.1693149,0.01921664,0.05679995],"study_design_scores_gemma":[0.0001730955,0.0001358204,0.0005367615,7.849504e-7,0.000003546743,0.00000559194,0.00006444448,0.8673375,0.000002061665,0.002173267,0.1294738,0.00009340647],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001074055,0.0001513476,0.994646,0.001077533,0.0004081316,0.0001541563,4.763562e-7,0.000698731,0.001789591],"genre_scores_gemma":[0.6876304,0.00001240392,0.307144,0.001664371,0.0001833267,0.0002551997,0.000009670014,0.00001533535,0.003085227],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6875019,"threshold_uncertainty_score":0.5337654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01289011320629912,"score_gpt":0.2219046421287478,"score_spread":0.2090145289224487,"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."}}