{"id":"W2040031114","doi":"10.1016/j.chroma.2012.01.078","title":"Comprehensive multidimensional separations for the analysis of petroleum","year":2012,"lang":"en","type":"review","venue":"Journal of Chromatography A","topic":"Analytical Chemistry and Chromatography","field":"Chemistry","cited_by":71,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Petroleum; Biochemical engineering; Multidimensional analysis; Instrumentation (computer programming); Multidimensional data; Computer science; Chemistry; Data mining; Engineering; Mathematics; Statistics","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":[0.001641025,0.002432898,0.002055914,0.003912731,0.0004181381,0.001277626,0.00204962,0.001210193,0.003039596],"category_scores_gemma":[0.001008828,0.0009096733,0.0006309138,0.004210937,0.001014969,0.002590671,0.001884476,0.003153468,0.004496025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008565811,"about_ca_system_score_gemma":0.001251146,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009254338,"about_ca_topic_score_gemma":0.002213155,"domain_scores_codex":[0.9993197,0.00006078197,0.00004289719,0.0001051321,0.0004038611,0.00006766314],"domain_scores_gemma":[0.9993476,0.0001489175,0.0001064997,0.00005201553,0.0002709742,0.00007393814],"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":[0.00008507972,0.0001479628,0.0001099494,0.006989363,0.000108838,0.0001082251,0.00003806565,0.0006748762,0.02588811,0.004214947,0.0210536,0.940581],"study_design_scores_gemma":[0.00003132475,0.000156074,0.0008994553,0.0008257456,0.0001357318,0.001105456,0.0000383009,0.0008450583,0.04020415,0.003274,0.9523969,0.00008786005],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000726758,0.9876029,0.008384378,0.0003236128,0.000443859,0.00003556919,0.00009685192,0.00008252776,0.002303603],"genre_scores_gemma":[0.003582886,0.9851027,0.006579838,0.0003452348,0.000365899,0.00003402028,0.0002335831,0.00002383618,0.003731979],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003912731,"threshold_uncertainty_score":0.01016849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05664520665205747,"score_gpt":0.3412320612017762,"score_spread":0.2845868545497187,"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."}}