{"id":"W2809729201","doi":"","title":"Optimal Air Pollution Control Strategies with Application to the Power Generation Sector","year":2006,"lang":"en","type":"article","venue":"12th Conference on Atmospheric Radiation/12th Conference on Cloud Physics (10-14 July 2006)","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Air pollution; Environmental science; Control (management); Pollution; Natural resource economics; Business; Environmental planning; Computer science; Economics; Artificial intelligence","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","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001224453,0.0007722061,0.0007316559,0.00005668573,0.0006866144,0.001061783,0.001290556,0.0002771928,0.001467297],"category_scores_gemma":[0.000348949,0.0005307581,0.000188261,0.001596119,0.000278309,0.0006173244,0.00005680626,0.000484219,0.002430575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003334081,"about_ca_system_score_gemma":0.001120871,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001920437,"about_ca_topic_score_gemma":0.0001000933,"domain_scores_codex":[0.9940969,0.0003505767,0.001094046,0.001426029,0.002211753,0.0008206408],"domain_scores_gemma":[0.99523,0.0005492066,0.0007546736,0.001576045,0.001589273,0.0003008274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002577313,0.0002259288,0.00005341923,0.000005374922,0.0000414405,0.00000275631,0.0002666506,0.759042,0.0009630756,0.1960422,0.03622453,0.006874896],"study_design_scores_gemma":[0.002678598,0.001859257,0.01013397,0.0001036446,0.0001226704,0.00000866779,0.0005937153,0.8983582,0.001034432,0.02089335,0.06261989,0.001593646],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02913559,0.0000698759,0.9430836,0.003892046,0.0008046147,0.001793304,0.0002179778,0.0002823804,0.02072057],"genre_scores_gemma":[0.987597,0.0000127912,0.003820885,0.001002115,0.001259202,0.0004511609,0.0001298187,0.00006784645,0.005659143],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9584615,"threshold_uncertainty_score":0.9999752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03133057246540033,"score_gpt":0.2697205181488617,"score_spread":0.2383899456834613,"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."}}