{"id":"W4390483489","doi":"10.23977/cpcs.2023.070115","title":"Optimization and Use of Cloud Computing in Big Data Science","year":2023,"lang":"en","type":"article","venue":"Computing Performance and Communication systems","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cloud computing; Big data; Computer science; Data science; Key (lock); Utility computing; Cloud computing security; Computer security; Data mining","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00293014,0.0006633947,0.0009099307,0.001150015,0.001097707,0.003902524,0.001047477,0.0008627911,0.001829808],"category_scores_gemma":[0.008650457,0.0004576526,0.0008832575,0.002442528,0.0009864231,0.003525021,0.00125718,0.001055674,0.0003075261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002686604,"about_ca_system_score_gemma":0.004252814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008301619,"about_ca_topic_score_gemma":0.006926305,"domain_scores_codex":[0.9979222,0.0009179836,0.00008646498,0.0001637075,0.0006435162,0.0002661024],"domain_scores_gemma":[0.9968044,0.001918293,0.00022921,0.0002472526,0.0005986069,0.0002022252],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002537298,0.0001860857,0.006400605,0.0003263642,0.000140319,0.0002031881,0.00007422003,0.7668574,0.003427525,0.1430061,0.004349127,0.07477523],"study_design_scores_gemma":[0.00001215239,0.00004529737,0.001299167,0.00004939534,0.00002952333,0.000042736,0.00006498036,0.951024,0.001505171,0.04248886,0.003422287,0.00001643274],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1173067,0.02308519,0.7498075,0.01191335,0.0009092211,0.0003565582,0.0002723653,0.0004252281,0.09592392],"genre_scores_gemma":[0.9267097,0.006036734,0.0633834,0.0003331751,0.0002286246,0.00008571855,0.00009285956,0.0001079362,0.003021764],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008301619,"threshold_uncertainty_score":0.01949275,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4672031048822616,"score_gpt":0.4858844733562521,"score_spread":0.01868136847399055,"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."}}