{"id":"W4293027991","doi":"10.3390/app12178397","title":"Development of an Intelligent Solution for the Optimization of Hybrid Energy Systems","year":2022,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Hybrid Renewable Energy Systems","field":"Energy","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"","keywords":"Computer science; Ontology; Installation; Structuring; Process (computing); Development (topology); Hybrid system; Software; Energy (signal processing); Software engineering; Systems engineering; Engineering; Mathematics; Machine learning; Programming language","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":[0.001377324,0.00009834755,0.0001819695,0.0001190631,0.0006329339,0.00002423506,0.0005628936,0.00001383783,0.00003716406],"category_scores_gemma":[0.00001417564,0.00007201912,0.00003911885,0.0004149899,0.0001662707,0.00006639732,0.0001174869,0.00003096681,4.948853e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008936691,"about_ca_system_score_gemma":0.0002289027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001535882,"about_ca_topic_score_gemma":0.0002178153,"domain_scores_codex":[0.9984365,0.00007234728,0.0004876272,0.0002551672,0.000541581,0.0002067961],"domain_scores_gemma":[0.9992138,0.0001356231,0.0003304471,0.0002238006,0.00006101455,0.00003532695],"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":[0.00001550002,0.00004209169,0.000002728641,0.00001561544,0.00001978633,1.226123e-7,0.000344985,0.9165918,0.007364735,0.06518048,0.000062051,0.01036014],"study_design_scores_gemma":[0.0001373963,0.00007565666,0.000003089146,0.00000745425,0.00001111866,0.000006076136,0.003121194,0.8434615,0.1195858,0.0001959657,0.03328418,0.0001105472],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06660946,0.0005393752,0.9232986,0.00004512044,0.001290102,0.0004789936,0.00001603128,0.00006158846,0.007660726],"genre_scores_gemma":[0.987106,0.000006444935,0.01211088,0.00001759401,0.00005635339,0.0004754953,0.00002773668,0.00001107938,0.0001883741],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9204966,"threshold_uncertainty_score":0.486808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03229232865367201,"score_gpt":0.2451329285751688,"score_spread":0.2128405999214968,"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."}}