{"id":"W3198364850","doi":"10.1021/acs.energyfuels.1c02091","title":"Applications of High Performance Liquid Chromatography in the Petroleomic Analysis of Crude Oil: A Mini-Review","year":2021,"lang":"en","type":"article","venue":"Energy & Fuels","topic":"Petroleum Processing and Analysis","field":"Chemistry","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Fourier transform ion cyclotron resonance; Chromatography; High-performance liquid chromatography; Mass spectrometry; Chemistry; Crude oil; High resolution; Analyte; Resolution (logic); Analytical Chemistry (journal); Computer science; Engineering; Artificial intelligence; Petroleum engineering","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":[0.001241968,0.001013658,0.001206544,0.002715566,0.0002879614,0.001235408,0.001006647,0.001098355,0.003087203],"category_scores_gemma":[0.001146303,0.0004102695,0.0007773352,0.003134706,0.0005155477,0.002323125,0.0007788349,0.00135673,0.002339858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005453309,"about_ca_system_score_gemma":0.001231855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007341849,"about_ca_topic_score_gemma":0.001121184,"domain_scores_codex":[0.9995798,0.00007001228,0.00006595983,0.00008498513,0.0001574887,0.00004162578],"domain_scores_gemma":[0.9989832,0.0004664835,0.0001475087,0.00002893614,0.0003096082,0.00006412347],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007424143,0.0001184678,0.0004472663,0.03037255,0.0002019487,0.0003014752,0.0001096479,0.000631523,0.01240293,0.003630231,0.02353643,0.9281731],"study_design_scores_gemma":[0.000009324044,0.0001816543,0.001503835,0.002663862,0.0002266763,0.001252165,0.00009161764,0.0002653675,0.005943078,0.001266711,0.9865447,0.00005103571],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003423074,0.9977037,0.0005976045,0.0002547188,0.0002850592,0.000008546316,0.00002765533,0.00001197524,0.0007684712],"genre_scores_gemma":[0.001008948,0.997287,0.0005454692,0.0002525845,0.0003011867,0.00001135452,0.00005728657,0.000003739317,0.000532378],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003087203,"threshold_uncertainty_score":0.0103277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006536254295119634,"score_gpt":0.2338879596843648,"score_spread":0.2273517053892451,"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."}}