{"id":"W4214548959","doi":"10.1109/tste.2019.2925442","title":"IEEE Transactions on Sustainable Energy","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Sustainable Energy","topic":"Energy Efficiency and Management","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Energy (signal processing); Computer science","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004612472,0.0009276158,0.0007569114,0.001409801,0.001249765,0.0002474136,0.0008355025,0.0005195176,0.003921443],"category_scores_gemma":[0.000008009914,0.0009503231,0.0006426812,0.001996686,0.0001824226,0.000848403,0.000004427699,0.0006454624,0.0003587638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001223025,"about_ca_system_score_gemma":0.0003742212,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01983622,"about_ca_topic_score_gemma":0.001344585,"domain_scores_codex":[0.9941,0.0002545861,0.0008316186,0.00143479,0.001001872,0.002377149],"domain_scores_gemma":[0.9968624,0.0003277975,0.0002163436,0.001654585,0.0004828434,0.0004561052],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003743139,0.001087732,3.606285e-7,0.0001316161,0.0002283077,0.0002450822,0.0001837331,0.7140919,0.0005686691,0.2603495,0.001396301,0.02134245],"study_design_scores_gemma":[0.00270654,0.001461201,0.000004414908,0.00008157747,0.0002214338,0.00002990932,0.00810233,0.01276173,0.1790454,0.005502572,0.7885532,0.001529695],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005820587,0.000140119,0.8276546,0.0004844879,0.001958908,0.0003680108,0.00001537806,0.0007935297,0.1627644],"genre_scores_gemma":[0.5938657,0.000243263,0.00009079609,0.001227785,0.00009520075,0.0004096614,0.00001001247,0.0001399633,0.4039176],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8275638,"threshold_uncertainty_score":0.9992948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006517135357169525,"score_gpt":0.2112813526422112,"score_spread":0.2047642172850416,"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."}}