{"id":"W2320415684","doi":"10.5383/ijtee.01.01.005","title":"Energy Use, Energy Savings and Environmental Analysis of Industrial","year":2010,"lang":"en","type":"article","venue":"International Journal of Thermal and Environmental Engineering","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Energy (signal processing); Environmental science; Energy analysis; Statistics; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002940286,0.0002492344,0.000154536,0.00186101,0.0002337239,0.0005518429,0.0002582291,0.0001882582,0.003694366],"category_scores_gemma":[0.0006687157,0.0001190369,0.0004770383,0.002415954,0.0001402073,0.0005211967,0.0002254387,0.0002035118,0.0006882744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001022361,"about_ca_system_score_gemma":0.0004027268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007331904,"about_ca_topic_score_gemma":0.01646458,"domain_scores_codex":[0.9993978,0.00008465921,0.00002100004,0.0000598989,0.0003726263,0.00006409382],"domain_scores_gemma":[0.9996507,0.0001169497,0.00006851908,0.00003673919,0.0001183305,0.000008726896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001281244,0.0006932133,0.4066963,0.0009635435,0.0003895679,0.0005436086,0.0002040353,0.1600797,0.02721351,0.007446788,0.005972998,0.3885156],"study_design_scores_gemma":[0.0000186823,0.0007448724,0.869269,0.0001114763,0.0001899335,0.0003777761,0.0007335278,0.04564801,0.03803069,0.004299837,0.04050357,0.00007264301],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9519283,0.001995687,0.004428633,0.0002061993,0.00002807916,0.00004815876,0.005211363,0.0001075407,0.03604602],"genre_scores_gemma":[0.988545,0.0008012464,0.001419356,0.00002467568,0.000007972912,0.00001942362,0.002584422,0.00002501233,0.006572803],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007331904,"threshold_uncertainty_score":0.01457846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005138340918260422,"score_gpt":0.181893162477098,"score_spread":0.1767548215588375,"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."}}