{"id":"W3168132687","doi":"10.1002/cjce.24213","title":"Oil fingerprint identification technology using a simplified set of biomarkers selected based on principal component difference","year":2021,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Petroleum Processing and Analysis","field":"Chemistry","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Natural Science Foundation of Shandong Province; National Natural Science Foundation of China","keywords":"Principal component analysis; Fingerprint (computing); Cluster analysis; Identification (biology); Set (abstract data type); Computer science; Data mining; Hierarchical clustering; Pattern recognition (psychology); Chemometrics; Artificial intelligence; Machine learning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0003799575,0.000692127,0.0007659354,0.0009914997,0.000245405,0.0006365044,0.0004930689,0.0003993153,0.0006229788],"category_scores_gemma":[0.0009147744,0.000208726,0.0005572931,0.0009150028,0.0003212322,0.0007999944,0.0006318477,0.0003486478,0.0003283284],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003264909,"about_ca_system_score_gemma":0.0006051378,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001380785,"about_ca_topic_score_gemma":0.001114193,"domain_scores_codex":[0.9994546,0.00006884043,0.00002961812,0.0001527514,0.0002571548,0.0000371032],"domain_scores_gemma":[0.9996881,0.00005184117,0.00007339894,0.00004310895,0.0001251295,0.00001841184],"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":[0.0004861043,0.0002602497,0.008621818,0.0004061104,0.0001562399,0.000193585,0.00007073811,0.06319837,0.6054795,0.00250447,0.001013284,0.3176095],"study_design_scores_gemma":[0.00005799507,0.0005163387,0.01181638,0.00001903074,0.0001978167,0.0003695034,0.0000491204,0.7228791,0.2577064,0.002329837,0.003937864,0.0001205438],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2209826,0.000807358,0.7756053,0.0001662539,0.00007667241,0.0001655544,0.0002659773,0.0007282243,0.001202062],"genre_scores_gemma":[0.6645144,0.0006363402,0.3322305,0.0001026425,0.00004458067,0.0001667167,0.0004491113,0.00003243121,0.001823214],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001380785,"threshold_uncertainty_score":0.002745509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.012381395216402,"score_gpt":0.2160296049457639,"score_spread":0.2036482097293619,"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."}}