{"id":"W4400943108","doi":"10.1016/j.colsurfa.2024.134917","title":"Synthesis of amphiphilic silicon quantum dots and its application in high efficiency imbibition oil recovery in low permeability reservoirs","year":2024,"lang":"en","type":"article","venue":"Colloids and Surfaces A Physicochemical and Engineering Aspects","topic":"Enhanced Oil Recovery Techniques","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Taishan Scholar Foundation of Shandong Province; National Natural Science Foundation of China","keywords":"Imbibition; Amphiphile; Quantum dot; Silicon; Permeability (electromagnetism); Chemical engineering; Teaching philosophy; Petroleum engineering; Materials science; Chemistry; Nanotechnology; Organic chemistry; Geology; Engineering; Membrane; Mathematics","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":[0.0001264329,0.0001585453,0.0001127502,0.0001267012,0.0001169786,0.0002072962,0.0001141888,0.0002927026,0.0005492697],"category_scores_gemma":[0.0001334416,0.00009919926,0.000143923,0.0001423596,0.0001397933,0.0002341193,0.000162524,0.0002132815,0.0001814735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002107647,"about_ca_system_score_gemma":0.0001568172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003391608,"about_ca_topic_score_gemma":0.0005854573,"domain_scores_codex":[0.9999529,0.000005120668,0.000004396197,0.00001365431,0.00001555003,0.000008442764],"domain_scores_gemma":[0.9999505,0.00001261232,0.00001173576,0.00000673775,0.00001158986,0.000006880417],"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":[0.00001527918,0.000007930433,0.00003909614,0.00003600186,0.000001747993,0.00002036143,0.00001380089,0.0001779858,0.9978866,0.0002681448,0.00001998361,0.001513018],"study_design_scores_gemma":[0.000002126224,0.00003713491,0.0001641332,0.00000137619,0.00000203359,0.0000173744,0.000004260204,0.000878446,0.9981262,0.00002603998,0.0007386334,0.000002255524],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9806101,0.001168063,0.01495428,0.0001096379,0.00002500747,0.00003972767,0.0001705092,0.00006988528,0.002852687],"genre_scores_gemma":[0.989854,0.0005497413,0.007873934,0.00002360277,0.00000407219,0.00002312726,0.00009313558,0.00001284229,0.001565368],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0005492697,"threshold_uncertainty_score":0.001837432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004075830337606797,"score_gpt":0.195033012956611,"score_spread":0.1909571826190042,"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."}}