{"id":"W4402673276","doi":"10.1109/mpe.2024.3428441","title":"Emissions Response: Efficient Decarbonization using Real-Time Data","year":2024,"lang":"en","type":"article","venue":"IEEE Power and Energy Magazine","topic":"Air Quality Monitoring and Forecasting","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Real-time data; Environmental science; Computer science; World Wide Web","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":[0.0004803554,0.0001128831,0.00009399115,0.00004282756,0.0001478806,0.00007029086,0.0001511403,0.00005503849,0.000334215],"category_scores_gemma":[0.00005908676,0.00009759737,0.00001900476,0.0002642863,0.00008459833,0.0001232538,0.0002255906,0.00006602503,0.0001116742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000815837,"about_ca_system_score_gemma":0.00001671715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002219792,"about_ca_topic_score_gemma":0.000004286122,"domain_scores_codex":[0.9989855,0.00007474164,0.0001618312,0.0003804158,0.0001942674,0.0002032998],"domain_scores_gemma":[0.9994034,0.0001115786,0.00002388029,0.0003447461,0.000005179258,0.0001112682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001877736,0.0001142418,0.001334428,0.00003070122,0.00004151102,0.000147952,0.001212562,0.05977171,0.8841699,0.0002819952,0.02140995,0.03129721],"study_design_scores_gemma":[0.0001355999,0.00005536991,0.003398842,0.000127846,0.00003543315,0.0000733093,0.00003689813,0.9093578,0.002457109,0.00007779758,0.08396459,0.0002794406],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9740716,0.0002236666,0.0119575,0.0002577211,0.0006954569,0.00002659153,0.0000250558,0.0001825006,0.0125599],"genre_scores_gemma":[0.9911069,0.00004029262,0.001543629,0.0000278881,0.0001179824,0.000001425916,0.00002199639,0.00002294503,0.007116885],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8817129,"threshold_uncertainty_score":0.3979906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02959852919476509,"score_gpt":0.2866096681055449,"score_spread":0.2570111389107799,"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."}}