{"id":"W3018825982","doi":"10.1109/smartnets48225.2019.9069765","title":"Google Traces Analysis for Deep Machine Learning Cloud Elastic Model","year":2019,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cistel Technology (Canada); Concordia University","funders":"","keywords":"Cloud computing; Computer science; Artificial intelligence; Deep learning; Operating system","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":[0.000749939,0.001192948,0.0005306026,0.003389851,0.0004417451,0.001170163,0.001181721,0.0004642845,0.002473644],"category_scores_gemma":[0.003041754,0.0002807201,0.0008903171,0.00298315,0.0002949945,0.001438542,0.0008458235,0.0007295625,0.0006184233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009915436,"about_ca_system_score_gemma":0.001195616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03896271,"about_ca_topic_score_gemma":0.02398803,"domain_scores_codex":[0.9994001,0.00007559905,0.00005476192,0.0001298866,0.0002513805,0.000088242],"domain_scores_gemma":[0.9993373,0.0001821674,0.00007606435,0.0001489474,0.0002262393,0.00002941839],"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":[0.0003796935,0.0002881736,0.04833901,0.0004468067,0.0002112797,0.0009598127,0.0003235317,0.6944274,0.00471899,0.01907201,0.02119792,0.2096353],"study_design_scores_gemma":[0.000005560228,0.00002622375,0.003690162,0.00001402314,0.0000108701,0.0000617249,0.00009142781,0.9872403,0.001595606,0.004507706,0.002743797,0.0000126721],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.459257,0.001254118,0.4735692,0.001372163,0.0002446668,0.0003994167,0.02569497,0.02474033,0.01346817],"genre_scores_gemma":[0.9096456,0.000577845,0.06408782,0.00008005865,0.00003529072,0.0002492965,0.02114211,0.0004153517,0.003766686],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03896271,"threshold_uncertainty_score":0.07747185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0120719070192789,"score_gpt":0.2251382492569885,"score_spread":0.2130663422377096,"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."}}