{"id":"W2947136163","doi":"10.3390/polym11060949","title":"Improving the Thermal Stability of Hydrophobic Associative Polymer Aqueous Solution Using a “Triple-Protection” Strategy","year":2019,"lang":"en","type":"article","venue":"Polymers","topic":"Enhanced Oil Recovery Techniques","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Key Research and Development Program of China; Southwest Petroleum University; State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation; National Natural Science Foundation of China","keywords":"Polymer; Polyacrylamide; Oxidizing agent; Materials science; Viscosity; Thermal stability; Aqueous solution; Chemical engineering; Wetting; Viscoelasticity; Composite material; Polymer chemistry; Chemistry; Organic 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002902125,0.0001510454,0.000181749,0.00006373416,0.00006345881,0.00001872809,0.000147323,0.0001201959,0.000160962],"category_scores_gemma":[0.00002313201,0.0001296509,0.000101898,0.0002150289,0.00005745527,0.0001789584,0.00003146098,0.0002488743,0.000007257681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003972494,"about_ca_system_score_gemma":0.00007267696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002036022,"about_ca_topic_score_gemma":0.00004291799,"domain_scores_codex":[0.9990208,0.00009285707,0.0002330434,0.0001607625,0.0001707253,0.0003217893],"domain_scores_gemma":[0.9994902,0.00006928312,0.0001170672,0.0002555655,0.00003255738,0.00003534331],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001625449,0.00001168942,0.0007119595,0.00004318215,0.00004289357,3.534116e-7,0.0004905949,0.001050534,0.9789167,0.00001977659,0.000002571101,0.01869349],"study_design_scores_gemma":[0.0001402906,0.00005822448,0.0009774151,0.00002002722,0.00001839303,0.000002629656,0.0002290361,0.1074021,0.8909712,0.00003880299,0.000004918009,0.0001369643],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897843,0.0008330786,0.00505552,0.00001285713,0.0002449475,0.0003313095,0.00001280515,0.0002456034,0.003479569],"genre_scores_gemma":[0.9995615,0.00001245863,0.0002156223,0.00001618588,0.0000403673,0.00002264529,0.000001344873,0.00003589409,0.00009398964],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1063516,"threshold_uncertainty_score":0.5287011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01525071219939408,"score_gpt":0.2207226891633975,"score_spread":0.2054719769640034,"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."}}