{"id":"W3016217006","doi":"10.1016/j.fuel.2020.117787","title":"Evaluation of crude oil asphaltene deposition inhibitors by surface plasmon resonance","year":2020,"lang":"en","type":"article","venue":"Fuel","topic":"Petroleum Processing and Analysis","field":"Chemistry","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"Ocean Frontier Institute; Canada Foundation for Innovation; Natural Sciences and Engineering Research Council of Canada; Marine Environmental Observation Prediction and Response Network","keywords":"Asphaltene; Surface plasmon resonance; Deposition (geology); Refractive index; Titration; Chemistry; Wavelength; Analytical Chemistry (journal); Crude oil; Heptane; Chromatography; Materials science; Nanotechnology; Inorganic chemistry; Nanoparticle; Organic chemistry; Optoelectronics; Geology; Petroleum engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002295788,0.00008895911,0.0001411272,0.00001150592,0.00004327185,0.00001786806,0.00009564612,0.00007449659,0.0001596208],"category_scores_gemma":[0.0001483977,0.00009081655,0.00005808442,0.0001666029,0.00002377274,0.00008404189,0.00001853683,0.00009623717,0.00001722798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005215475,"about_ca_system_score_gemma":0.00006196001,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005058838,"about_ca_topic_score_gemma":0.000006152751,"domain_scores_codex":[0.9988505,0.0000337612,0.0002069833,0.0002074511,0.0005869773,0.0001142881],"domain_scores_gemma":[0.9994872,0.00002225954,0.0001385463,0.0001142985,0.0001755807,0.00006211034],"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":[0.00002301156,0.00004324746,0.0009436427,0.0001823352,0.00002722825,8.851741e-7,0.0001687321,0.0006399912,0.9397016,0.000001487944,0.001544353,0.05672356],"study_design_scores_gemma":[0.0005681838,0.00001601618,0.00007222742,0.0001096162,0.0001974382,8.168811e-7,0.00009605908,0.0370041,0.958818,0.00002686618,0.002972224,0.0001184232],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9738951,0.006950555,0.00006084641,0.0004928177,0.0000219687,0.00000294728,0.00003339387,0.00004950159,0.01849283],"genre_scores_gemma":[0.9983846,0.0001127799,0.0002233805,0.00007207356,0.00008081098,0.000004148186,0.00006873647,0.00001166007,0.001041819],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05660513,"threshold_uncertainty_score":0.3703392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02101982637247872,"score_gpt":0.2550656779122195,"score_spread":0.2340458515397407,"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."}}