{"id":"W4312385468","doi":"10.2139/ssrn.4261893","title":"Screening of Waterflooding Using Smart Proxy Model Coupled with Deep Convolutional Neural Network","year":2022,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Hydrological Forecasting Using AI","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Proxy (statistics); Convolutional neural network; Computer science; Artificial intelligence; Petroleum engineering; Geology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003265124,0.0006503657,0.0007086425,0.0009303768,0.0003108822,0.0007066469,0.0008011211,0.001119232,0.001770934],"category_scores_gemma":[0.001550391,0.0003694309,0.0006326136,0.00087807,0.0002136163,0.00111688,0.0005207203,0.0005050171,0.0003790126],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004373724,"about_ca_system_score_gemma":0.0009618683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02129932,"about_ca_topic_score_gemma":0.02036328,"domain_scores_codex":[0.9998635,0.00001655964,0.00000680339,0.00004693976,0.00002725925,0.00003889277],"domain_scores_gemma":[0.9995907,0.0001458991,0.00004314481,0.00004751118,0.0001116518,0.00006117476],"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":[0.0004909671,0.0002624443,0.07334852,0.0001782815,0.0001824001,0.000781748,0.00006249288,0.8298868,0.01762142,0.001386038,0.003818314,0.07198051],"study_design_scores_gemma":[0.000006592639,0.000009639562,0.002003654,0.000002644393,0.000009167658,0.000008226617,0.00001037339,0.9964844,0.001167722,0.0002091444,0.0000830714,0.000005307853],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9169539,0.0004101823,0.07603446,0.0003812942,0.0001130339,0.00003647529,0.001773914,0.001380108,0.002916735],"genre_scores_gemma":[0.9896559,0.00009129725,0.008334393,0.00003451499,0.00001466609,0.000007529071,0.001011977,0.00003367435,0.0008160557],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02129932,"threshold_uncertainty_score":0.04235071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01726014297407583,"score_gpt":0.2193943320244778,"score_spread":0.2021341890504019,"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."}}