{"id":"W4361186953","doi":"10.1016/j.geoen.2023.211727","title":"Enhancement of CO2 viscosity prediction using advanced intelligent methods: Application to carbon capture and storage","year":2023,"lang":"en","type":"article","venue":"Geoenergy Science and Engineering","topic":"Carbon Dioxide Capture Technologies","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Machine learning; Artificial intelligence; Multilayer perceptron; Pipeline (software); Data mining; Random forest; Viscosity; Artificial neural network","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":[0.0003959959,0.0001200366,0.0001445605,0.0003593642,0.00002517157,0.000020045,0.0001196412,0.00005418857,3.912475e-7],"category_scores_gemma":[0.00008836588,0.0001248429,0.00001253974,0.001057658,0.00006877421,0.0001276921,0.0001156967,0.00008353282,2.923169e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001204942,"about_ca_system_score_gemma":0.00001380029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005636143,"about_ca_topic_score_gemma":0.000006534313,"domain_scores_codex":[0.99918,0.000003938277,0.0001553175,0.0002318395,0.0001873504,0.0002415065],"domain_scores_gemma":[0.9996347,0.00002377298,0.0000207894,0.0001912204,0.00005375351,0.00007572299],"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":[9.062044e-7,0.000001027645,0.00002421473,0.00002845376,0.000003393,3.63743e-7,0.0001459944,0.4458123,0.5453024,0.0001413116,0.000002361375,0.008537329],"study_design_scores_gemma":[0.00003675171,0.00001519463,0.001234689,0.00003127956,0.00000578703,0.000002943957,0.0001822831,0.6734451,0.3245392,0.00002006824,0.000394486,0.00009226355],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8287676,0.0004668906,0.1699712,0.00001968482,0.0002007657,0.0001205515,0.000002375268,0.000399674,0.00005123749],"genre_scores_gemma":[0.9876239,0.0001857128,0.01212054,0.000006507174,0.00001633378,0.00002728713,0.000001460727,0.00001288219,0.000005322348],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2276328,"threshold_uncertainty_score":0.5090944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009489070036703314,"score_gpt":0.2456663521711529,"score_spread":0.2361772821344496,"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."}}