{"id":"W4236171033","doi":"10.32920/ryerson.14663814","title":"Effect of pressure variation on polymer flooding","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Enhanced Oil Recovery Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Enhanced oil recovery; Oil in place; Polyacrylamide; Polymer; Petroleum engineering; Brine; Materials science; Produced water; Porous medium; Residual oil; Oil field; Porosity; Chemical engineering; Environmental science; Composite material; Chemistry; Geology; Petroleum; Organic chemistry; Polymer chemistry","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":[0.0001988317,0.0004191743,0.0002244771,0.000173828,0.0001665517,0.0002604332,0.000351939,0.0002899941,0.001200826],"category_scores_gemma":[0.0008751283,0.0002021227,0.0001159759,0.0002590792,0.0002972222,0.0004761257,0.0003461391,0.0003669551,0.0002173707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001467052,"about_ca_system_score_gemma":0.0001838028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003831201,"about_ca_topic_score_gemma":0.0003287939,"domain_scores_codex":[0.9997854,0.00002750298,0.00001352185,0.00005031667,0.00008173412,0.00004161648],"domain_scores_gemma":[0.9996208,0.0001980945,0.00009495235,0.00002444858,0.00004157441,0.00002001729],"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":[0.0001462227,0.0000364705,0.0004308735,0.00007561145,0.000005452852,0.0001445591,0.00006048599,0.0006816609,0.9941215,0.00008816132,0.00007119518,0.004137823],"study_design_scores_gemma":[0.000004256528,0.0001745179,0.00131167,0.000002890711,0.000005111869,0.00004186273,0.00002062596,0.002924225,0.994948,0.00002070779,0.0005400476,0.000006044769],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994481,0.0004570584,0.003514999,0.00006068573,0.00001954018,0.00001722469,0.0001077841,0.0001797003,0.001162092],"genre_scores_gemma":[0.9976647,0.0003243179,0.001447129,0.00001883629,0.000007074281,0.00001759159,0.00005422201,0.00002514867,0.0004410407],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001200826,"threshold_uncertainty_score":0.004017174,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004704116721309296,"score_gpt":0.2324834041822537,"score_spread":0.2277792874609444,"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."}}