{"id":"W3004316630","doi":"10.1016/j.seta.2020.100644","title":"An intelligent load management application for solar boiler system","year":2020,"lang":"en","type":"article","venue":"Sustainable Energy Technologies and Assessments","topic":"Solar Radiation and Photovoltaics","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Boiler (water heating); Scheduling (production processes); Artificial neural network; Environmental science; Meteorology; Solar energy; Simulation; Computer science; Engineering; Real-time computing; Waste management; Operations management; Artificial intelligence; Electrical 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":[0.0001932001,0.0007770268,0.0004985894,0.0005375852,0.0004008357,0.0005268372,0.000657843,0.0005108723,0.0106652],"category_scores_gemma":[0.0003552522,0.000287346,0.0002284278,0.0003552623,0.00008397746,0.0004776077,0.0003650718,0.0003492959,0.001871377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001930224,"about_ca_system_score_gemma":0.0001826625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001751812,"about_ca_topic_score_gemma":0.002408287,"domain_scores_codex":[0.999886,0.00001614979,0.000007705292,0.0000267398,0.00005139133,0.00001189023],"domain_scores_gemma":[0.9998441,0.00004631464,0.00001186093,0.00002557337,0.00005165549,0.00002054357],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001859614,0.0006216776,0.008873495,0.0008721872,0.0001498675,0.002024006,0.0008449136,0.04936634,0.224389,0.00214254,0.06065105,0.6482053],"study_design_scores_gemma":[0.0002490846,0.0003068919,0.01336166,0.00006869085,0.0001496198,0.0007189749,0.000166675,0.8206784,0.1054348,0.001833577,0.05693157,0.0001000425],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2628908,0.001029054,0.4874105,0.0006554993,0.0004168114,0.0006343382,0.002064949,0.1996538,0.04524432],"genre_scores_gemma":[0.8980438,0.000359276,0.07087673,0.0002302283,0.0001000438,0.0001721937,0.001148983,0.001595657,0.02747301],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0106652,"threshold_uncertainty_score":0.03567868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01097693253878274,"score_gpt":0.2629705321491741,"score_spread":0.2519935996103914,"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."}}