{"id":"W3179956343","doi":"","title":"PhysarumSM: P2P Service Discovery and Allocation in Dynamic Edge Networks","year":2021,"lang":"en","type":"article","venue":"Integrated Network Management","topic":"Slime Mold and Myxomycetes Research","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Microservices; Computer science; Orchestration; Cloud computing; Service discovery; Quality of service; Distributed computing; Computer network; Virtualization; Service (business); Enhanced Data Rates for GSM Evolution; Latency (audio); Web service; Operating system; World Wide Web; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000168654,0.0001812716,0.0001764806,0.00009359195,0.00004371246,0.0001468345,0.0001457984,0.0000767541,0.00003873289],"category_scores_gemma":[0.000004575459,0.0001799896,0.00003009401,0.001040968,0.00001749929,0.000174559,0.000136423,0.0002902713,0.00002285229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001475937,"about_ca_system_score_gemma":0.00001265229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000440925,"about_ca_topic_score_gemma":0.001034305,"domain_scores_codex":[0.9988591,0.00005366706,0.0002169019,0.0002777467,0.0001445024,0.0004481025],"domain_scores_gemma":[0.9995569,0.00004454885,0.00001645417,0.0002708119,0.0000509015,0.00006038163],"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":[0.00002801526,0.00005790158,0.00369868,0.0002443746,0.0002194829,0.0002403169,0.0001160127,0.8895791,0.0003374684,0.001748151,0.01057118,0.0931593],"study_design_scores_gemma":[0.000510032,0.00001536894,0.02791874,0.0003205581,0.00002739341,0.000006635968,0.0003586654,0.9537025,0.00011703,0.000455028,0.01629519,0.000272877],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8681168,0.02507706,0.04434439,0.002213261,0.002861195,0.001760421,0.0000185042,0.001068622,0.05453978],"genre_scores_gemma":[0.9939771,0.003498162,0.0005809608,0.0003366398,0.00009857841,0.00006988443,0.000147302,0.00003904631,0.001252337],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1258603,"threshold_uncertainty_score":0.7339762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006960465321422824,"score_gpt":0.2200415085190118,"score_spread":0.213081043197589,"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."}}