{"id":"W168892106","doi":"","title":"Energy and environmental advantages of cogeneration with nuclear and coal electrical utilities","year":2009,"lang":"en","type":"article","venue":"International Conference on Energy & Environment","topic":"Integrated Energy Systems Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Cogeneration; Coal; Fossil fuel; Environmental science; Waste management; Greenhouse gas; Electric potential energy; Electricity generation; Engineering; Energy (signal processing); Geology","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":[0.00003127127,0.0001747226,0.0001451911,0.0001002802,0.00003507948,0.00002903673,0.00007851612,0.00007583323,0.0001624845],"category_scores_gemma":[0.000001433763,0.0001594761,0.00001838437,0.00001900535,0.00008524695,0.000124368,0.00001180566,0.00005817888,0.000001224173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008188365,"about_ca_system_score_gemma":0.000005782017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004679796,"about_ca_topic_score_gemma":0.00001535931,"domain_scores_codex":[0.9991935,0.00002500264,0.000201662,0.0002058018,0.0002481818,0.0001258644],"domain_scores_gemma":[0.9997637,0.00001535532,0.0000523395,0.0001039109,0.000008562693,0.00005612712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002873226,0.0002147906,0.0009154096,0.0000100862,0.0002550094,0.00002252702,0.0003131993,0.3122906,0.08601529,0.5038071,0.000150959,0.09571765],"study_design_scores_gemma":[0.0007327043,0.0007209495,0.004472475,0.00005908067,0.00002586631,0.000050627,0.0002698977,0.9523532,0.03106059,0.0006727931,0.009207845,0.0003739129],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8787348,0.0008332352,0.08518413,0.0005031408,0.0002582831,0.0001484504,0.0001224651,0.0001821392,0.03403333],"genre_scores_gemma":[0.996667,0.002215137,0.0005928843,0.00009149504,0.00003911707,0.000006767127,0.0001226344,0.00001649212,0.0002484935],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6400626,"threshold_uncertainty_score":0.6503247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005798718571357957,"score_gpt":0.1762992392758293,"score_spread":0.1705005207044714,"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."}}