{"id":"W2558941480","doi":"10.1016/b978-0-12-809413-6.00004-7","title":"Chemical Fingerprints of Crude Oils and Petroleum Products","year":2016,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Petroleum Processing and Analysis","field":"Chemistry","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Petroleum; Biochemical engineering; Identification (biology); Oil spill; Environmental science; Petroleum product; Petroleum engineering; Computer science; Chemistry; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001474269,0.0004537442,0.0008080986,0.0001204661,0.00005913903,0.00003425812,0.0003286305,0.0004227489,0.0004714515],"category_scores_gemma":[0.00008047094,0.0003680776,0.0002231547,0.000009749283,0.0003183954,0.00003359465,0.0001951665,0.0004272122,0.00005344217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006440911,"about_ca_system_score_gemma":0.000141577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":2.739301e-7,"about_ca_topic_score_gemma":8.329224e-7,"domain_scores_codex":[0.9980615,0.000006737575,0.0005339372,0.000698164,0.0003860905,0.0003135497],"domain_scores_gemma":[0.9985195,0.00005905586,0.0004640969,0.0006634466,0.0001467763,0.0001470887],"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":[0.00001744654,0.00000896167,0.00001392241,0.0006825972,0.0001706111,0.00001212643,0.00003871652,1.494714e-8,0.2932342,0.0002690543,0.00002546457,0.7055269],"study_design_scores_gemma":[0.0004040512,0.000009864209,0.00000161114,0.002257117,0.0003784047,0.00002832276,0.000003625085,0.000001684581,0.2797834,0.001813568,0.714777,0.0005413694],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.009200606,0.002190599,0.000001456938,0.0001051082,0.00004526032,0.00001275654,0.00006378074,0.00006840614,0.988312],"genre_scores_gemma":[0.03415808,0.000158799,0.0002079784,0.00003842606,0.0004693993,0.00001180965,0.00001462439,0.00008368392,0.9648572],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.7147515,"threshold_uncertainty_score":0.9998771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01052195369829669,"score_gpt":0.2206783849544368,"score_spread":0.2101564312561401,"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."}}