{"id":"W3205200024","doi":"10.1007/s12652-021-03528-8","title":"LE2ML: a microservices-based machine learning workbench as part of an agnostic, reliable and scalable architecture for smart homes","year":2021,"lang":"en","type":"article","venue":"Journal of Ambient Intelligence and Humanized Computing","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Microservices; Workbench; Computer science; Scalability; Computational intelligence; Architecture; Software engineering; Artificial intelligence; Computer architecture; Distributed computing; Operating system; Cloud computing; Visualization","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001084545,0.0001902126,0.0005126073,0.0002214826,0.0003201834,0.0003785815,0.0003847734,0.00007120648,0.00002167677],"category_scores_gemma":[0.0002360366,0.0001761649,0.0001284407,0.0003174322,0.00006488785,0.0003963385,0.0002047689,0.0003627869,0.000001746129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002807605,"about_ca_system_score_gemma":0.0001691221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009643661,"about_ca_topic_score_gemma":0.00008897181,"domain_scores_codex":[0.9981378,0.0001475123,0.0007503677,0.0003567589,0.0003202731,0.0002872266],"domain_scores_gemma":[0.9973036,0.0007961717,0.0007532276,0.0002274844,0.0007637425,0.0001557531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005670296,0.001217618,0.02217878,0.001505799,0.0004613551,0.0003103552,0.0129229,0.0269192,0.03688656,0.003139891,0.000226229,0.8936643],"study_design_scores_gemma":[0.003378288,0.004592697,0.002510295,0.005365461,0.0002102733,0.002460723,0.002590277,0.6446927,0.2989898,0.01180981,0.02227858,0.001121093],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6093987,0.002133411,0.3876129,0.0002817258,0.0003222919,0.0001623409,0.000002614112,0.00002753772,0.00005843694],"genre_scores_gemma":[0.9636288,0.0001056436,0.03576979,0.0002728994,0.0001252211,0.000002172331,0.000005056361,0.00001480871,0.00007558983],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8925432,"threshold_uncertainty_score":0.7183794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02943022613178992,"score_gpt":0.2770400784282138,"score_spread":0.2476098522964238,"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."}}