{"id":"W4389988042","doi":"10.1021/acs.energyfuels.3c03056","title":"High Throughput Prescreening of Asphaltene Chemical Inhibitors Using Molecular Dynamics Approach","year":2023,"lang":"en","type":"article","venue":"Energy & Fuels","topic":"Petroleum Processing and Analysis","field":"Chemistry","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs; Equinor","keywords":"Asphaltene; Molecular dynamics; Throughput; Chemistry; Computational chemistry; Computer science; Organic chemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002488837,0.0006438307,0.0007608185,0.0003319612,0.0003852917,0.0005051268,0.0006103907,0.0005291293,0.001143221],"category_scores_gemma":[0.0005089045,0.0003211924,0.000458468,0.0002851211,0.0001858626,0.0005526762,0.0004025353,0.0007105888,0.0002662638],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004871917,"about_ca_system_score_gemma":0.0007987265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003010517,"about_ca_topic_score_gemma":0.003868107,"domain_scores_codex":[0.9999044,0.00001285661,0.000005852255,0.00001930109,0.00003782785,0.00001977539],"domain_scores_gemma":[0.9998448,0.0000648479,0.00002321464,0.00001275249,0.00003407046,0.00002029236],"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":[0.0005378202,0.0006790329,0.006585531,0.0008032017,0.0002646327,0.0003789406,0.0001417016,0.5437268,0.3995898,0.006324331,0.001945659,0.03902269],"study_design_scores_gemma":[0.00003591771,0.0001343345,0.0005590874,0.00000647646,0.0000325468,0.00002211634,0.00001709723,0.9496139,0.04762158,0.0004365045,0.001504202,0.00001622644],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8492232,0.002190585,0.1380688,0.0004789438,0.00009675558,0.0002141884,0.0008819611,0.001636726,0.007208792],"genre_scores_gemma":[0.8916752,0.001476431,0.1036079,0.0001055163,0.00001640732,0.0004660237,0.0009883333,0.0001310099,0.001533094],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003010517,"threshold_uncertainty_score":0.005985975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01310786987550216,"score_gpt":0.2354159928926711,"score_spread":0.2223081230171689,"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."}}