{"id":"W4366598528","doi":"10.1088/1742-6596/2474/1/012083","title":"Calculation of Emission Factors of the Northwest Regional Grid Based on Linear Support Vector Machines","year":2023,"lang":"en","type":"article","venue":"Journal of Physics Conference Series","topic":"Electric Power System Optimization","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"123 Certification (Canada)","funders":"","keywords":"Support vector machine; Status quo; Grid; Power grid; Regression analysis; Linear regression; Computer science; Regression; Correlation coefficient; Data mining; Power (physics); Statistics; Mathematics; Machine learning","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":[0.0001173083,0.0001064606,0.0002193966,0.00008609782,0.00003207929,0.000008816203,0.0001495368,0.00004592927,0.00001263492],"category_scores_gemma":[0.00005178572,0.00007269688,0.0001086496,0.000408037,0.00003463426,0.000187429,0.00001123096,0.0001335429,8.952024e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003139527,"about_ca_system_score_gemma":0.000137729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001281819,"about_ca_topic_score_gemma":0.00000776281,"domain_scores_codex":[0.9990788,0.00003685896,0.0003763981,0.00005534023,0.0003589291,0.00009374211],"domain_scores_gemma":[0.9991252,0.00007192031,0.000330422,0.0001354517,0.0003034761,0.00003352066],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000115738,0.00008786052,0.06004934,0.0003888372,0.0001079822,0.000003903193,0.001655842,0.8533974,0.07695493,0.001606187,0.001468114,0.004163856],"study_design_scores_gemma":[0.0005040522,0.000435297,0.139216,0.0005735858,0.00005917202,0.000007603003,0.0001282946,0.2619103,0.5960894,0.0004318805,0.0004316517,0.0002127363],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9804255,0.00001688155,0.01814876,0.0002201008,0.0007965446,0.0001202192,0.00004089818,0.00004240969,0.0001886405],"genre_scores_gemma":[0.9995896,0.0000264683,0.0001763754,0.000004087258,0.0001179515,8.340039e-7,0.00002462,0.00001481558,0.00004523622],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5914871,"threshold_uncertainty_score":0.2964493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01961485214053968,"score_gpt":0.2328021619825575,"score_spread":0.2131873098420178,"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."}}