{"id":"W3021667500","doi":"10.3390/en13092250","title":"Adaptive Machine Learning for Automated Modeling of Residential Prosumer Agents","year":2020,"lang":"en","type":"article","venue":"Energies","topic":"Data Stream Mining Techniques","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal; Université du Québec à Trois-Rivières","funders":"","keywords":"Prosumer; Forgetting; Computer science; Adaptation (eye); Concept drift; Quality (philosophy); Artificial intelligence; Machine learning; Data stream mining; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001156383,0.00009688996,0.0001494966,0.0000569738,0.0000652765,0.00005528059,0.0005948097,0.00003630121,0.000003733309],"category_scores_gemma":[0.0001431874,0.00009279927,0.0000479364,0.0001733279,0.00002235474,0.0003535939,0.0003750544,0.00007117257,0.000002765672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001057989,"about_ca_system_score_gemma":0.00003432368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001437762,"about_ca_topic_score_gemma":0.000004973755,"domain_scores_codex":[0.9991922,0.00003915941,0.0001941549,0.0002588267,0.0001655767,0.0001500297],"domain_scores_gemma":[0.9995459,0.00004245425,0.0000969634,0.0002032566,0.00007196543,0.0000395093],"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":[0.0001255717,0.00006031958,0.0004768092,0.00010392,0.0001177356,0.00001581575,0.005449149,0.9246399,0.01209401,0.02742423,0.01506314,0.01442933],"study_design_scores_gemma":[0.0001563336,0.0001560734,0.0000345363,0.00002508035,0.000006795429,8.339308e-7,0.00003392758,0.9785728,0.02000563,0.0004215567,0.0004925832,0.00009382253],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04372696,0.0001087465,0.9533322,0.0003625651,0.00007181421,0.0001586986,0.00001740329,0.001896339,0.000325284],"genre_scores_gemma":[0.7444089,0.000007735875,0.2554193,0.0000477518,0.00002530708,0.00002081811,0.00001629657,0.000009649248,0.0000442542],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7006819,"threshold_uncertainty_score":0.3784244,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05212651095589332,"score_gpt":0.2855728694845557,"score_spread":0.2334463585286624,"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."}}