{"id":"W2939608023","doi":"10.1145/3312614.3312643","title":"Metis","year":2019,"lang":"en","type":"article","venue":"","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metis; Computer science; Cloud computing; Node (physics); Task (project management); Metric (unit); Edge computing; Distributed computing; Enhanced Data Rates for GSM Evolution; Operating system; Systems engineering; Database; Artificial intelligence; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00009053006,0.0000360543,0.00004686421,0.0000273952,0.00002371438,0.00006234986,0.0003653865,0.00001441192,0.00003135612],"category_scores_gemma":[0.000003635404,0.0000288924,0.00002269045,0.0001267763,0.000003102965,0.0001570096,0.0001724857,0.00003370868,0.002584605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006387462,"about_ca_system_score_gemma":0.00001153605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001241594,"about_ca_topic_score_gemma":1.506653e-7,"domain_scores_codex":[0.9996041,0.00000826748,0.00005337561,0.0001307047,0.00007802773,0.0001255076],"domain_scores_gemma":[0.9996728,0.00002644592,0.00001141966,0.0002481047,0.00001500414,0.00002624031],"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":[0.000001517924,0.00004778346,0.02008173,0.00001828541,0.00002081893,0.0000133056,0.001130919,0.00003455835,0.003189335,0.2514598,0.2143308,0.5096711],"study_design_scores_gemma":[0.0003718901,0.00009525926,0.01609078,0.00001353993,0.000001813896,0.00002398314,0.00001103855,0.2219406,0.009612248,0.009374604,0.7421008,0.0003634128],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09152402,0.00003152525,0.5203681,0.0008279413,0.01195561,0.00006193379,4.451036e-9,0.0002970449,0.3749338],"genre_scores_gemma":[0.8203633,0.000001504408,0.1494565,0.001644469,0.001076419,0.000001240416,3.396407e-7,0.000006646745,0.02744955],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7288393,"threshold_uncertainty_score":0.998192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00503291203582265,"score_gpt":0.1914116631059535,"score_spread":0.1863787510701308,"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."}}