{"id":"W2013253797","doi":"10.1016/j.engappai.2010.06.012","title":"A comparison of two data analysis techniques and their applications for modeling the carbon dioxide capture process","year":2010,"lang":"en","type":"article","venue":"Engineering Applications of Artificial Intelligence","topic":"Carbon Dioxide Capture Technologies","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Regina","funders":"Canada Research Chairs","keywords":"Computer science; Process (computing); Carbon dioxide; Process engineering; Data mining; Programming language","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002740553,0.0001706094,0.0003163583,0.0002569425,0.00003337529,0.00001967887,0.0009138836,0.0001110425,9.603954e-7],"category_scores_gemma":[0.00006971645,0.0001428884,0.00006543472,0.0009791333,0.0001261583,0.00006276589,0.000104731,0.0002986899,1.812986e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001237273,"about_ca_system_score_gemma":0.00001481515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006409941,"about_ca_topic_score_gemma":0.0001145997,"domain_scores_codex":[0.9989763,0.000003663288,0.0004850507,0.000268242,0.0001063701,0.0001603614],"domain_scores_gemma":[0.9983244,0.0002113834,0.00009140686,0.001189949,0.0001493602,0.00003351029],"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":[0.000003505396,0.00004100854,0.00009316859,0.0001651057,0.0001735398,3.270776e-8,0.0005682236,0.7738053,0.1652435,0.02563203,0.000002449336,0.03427206],"study_design_scores_gemma":[0.000006595172,0.000004449313,0.000002271554,0.000006861585,0.00008958449,9.517606e-7,0.0004051893,0.676054,0.3202999,0.002808142,0.0002269679,0.00009509172],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05622973,0.000717256,0.9414582,0.00006775966,0.00002394764,0.0008991085,0.00008374359,0.0004531357,0.00006711487],"genre_scores_gemma":[0.9684159,0.00002512321,0.03029912,0.000001431495,0.0000603426,0.001141623,0.00002824157,0.00002713144,0.000001108737],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9121861,"threshold_uncertainty_score":0.5826821,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03617838724407821,"score_gpt":0.3235821207633919,"score_spread":0.2874037335193137,"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."}}