{"id":"W2294710185","doi":"10.1109/icmla.2015.152","title":"MLaaS: Machine Learning as a Service","year":2015,"lang":"en","type":"article","venue":"","topic":"Time Series Analysis and Forecasting","field":"Computer Science","cited_by":383,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Scalability; Context (archaeology); Architecture; Service (business); Information extraction; Data science; Social media; Electricity; World Wide Web; The Internet; Big data; Machine learning; Artificial intelligence; Multimedia; Data mining; Database; Engineering","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":[0.002967929,0.001650412,0.001928679,0.002553736,0.001033766,0.005445105,0.005286095,0.004228629,0.06333657],"category_scores_gemma":[0.01568071,0.0009861534,0.001346807,0.003500467,0.0008667021,0.006918375,0.005626676,0.004189815,0.05847438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001847286,"about_ca_system_score_gemma":0.003312046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004614673,"about_ca_topic_score_gemma":0.002609382,"domain_scores_codex":[0.9970096,0.0005576353,0.0002723132,0.0004356532,0.001359969,0.0003647845],"domain_scores_gemma":[0.9921538,0.002180091,0.0003592309,0.002663416,0.001603432,0.001039974],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00160661,0.0005520786,0.001658227,0.0006130406,0.0002260587,0.0008225653,0.0002572027,0.01202579,0.007848082,0.02061335,0.6469688,0.3068081],"study_design_scores_gemma":[0.0005608649,0.0002279066,0.001241511,0.0002003952,0.00005802018,0.0005164703,0.0001404362,0.415579,0.01308726,0.071817,0.4963327,0.000238482],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.003639146,0.001092035,0.268985,0.002504871,0.0009045763,0.0005641847,0.009530806,0.6894932,0.02328623],"genre_scores_gemma":[0.2909951,0.004726418,0.4259682,0.0113621,0.002872595,0.002911781,0.09719197,0.07048617,0.09348571],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.06333657,"threshold_uncertainty_score":0.2118819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03180556607227813,"score_gpt":0.2346453364751164,"score_spread":0.2028397704028382,"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."}}