{"id":"W3176971075","doi":"10.1007/s10664-021-09994-0","title":"MLASP: Machine learning assisted capacity planning","year":2021,"lang":"en","type":"article","venue":"Empirical Software Engineering","topic":"Software System Performance and Reliability","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University; Top Hat (Canada)","funders":"","keywords":"Computer science; Capacity planning; Artificial intelligence; 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":[0.001090033,0.001088616,0.0007585208,0.001593992,0.000484097,0.001480551,0.002094393,0.001122032,0.02848948],"category_scores_gemma":[0.006702336,0.0006835685,0.0008238209,0.001126423,0.000413942,0.001937169,0.001466278,0.001927766,0.007126191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007497993,"about_ca_system_score_gemma":0.001918698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007995283,"about_ca_topic_score_gemma":0.01172369,"domain_scores_codex":[0.9994187,0.0001863264,0.00003126992,0.0001098649,0.0001826115,0.00007126655],"domain_scores_gemma":[0.997857,0.001116486,0.0001225424,0.0003477052,0.0004194145,0.0001367965],"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":[0.0003646902,0.0002720625,0.002006347,0.0002955555,0.0001274741,0.0002023197,0.00008880211,0.5054069,0.001655086,0.01797114,0.1330965,0.3385131],"study_design_scores_gemma":[0.00003078712,0.00002303506,0.0001802816,0.00001117043,0.000008097789,0.00002176546,0.00001045393,0.9795782,0.001321149,0.01322284,0.005580467,0.00001178816],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01247885,0.0003876792,0.8329028,0.0007517913,0.0003864043,0.0003120713,0.008658398,0.1281152,0.01600694],"genre_scores_gemma":[0.3348296,0.0002578418,0.6388623,0.0003271365,0.0002112048,0.0006476879,0.009240511,0.003835706,0.01178799],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02848948,"threshold_uncertainty_score":0.09530675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03252904706006558,"score_gpt":0.2610161678821591,"score_spread":0.2284871208220935,"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."}}