{"id":"W2052391546","doi":"10.1007/s00216-011-5130-0","title":"Using GC × GC-FID profiles to estimate the age of weathered gasoline samples","year":2011,"lang":"en","type":"article","venue":"Analytical and Bioanalytical Chemistry","topic":"Analytical Chemistry and Chromatography","field":"Chemistry","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; University of Alberta","keywords":"Partial least squares regression; Gasoline; Weathering; Multivariate statistics; Sample (material); Linear discriminant analysis; Environmental science; Statistics; Chemistry; Environmental chemistry; Mathematics; Chromatography; Geology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003588916,0.000510941,0.0002498804,0.001259902,0.0003626622,0.0004485964,0.0004279868,0.000584096,0.0006800866],"category_scores_gemma":[0.001061579,0.000221182,0.0003111256,0.0005864556,0.0002002432,0.0005240336,0.0001903917,0.0004184268,0.0005878376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004726814,"about_ca_system_score_gemma":0.0003474101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009564096,"about_ca_topic_score_gemma":0.02320533,"domain_scores_codex":[0.9997067,0.00002018834,0.00001859447,0.0001181368,0.0001141168,0.00002224467],"domain_scores_gemma":[0.999468,0.0001091346,0.0001046898,0.00003634312,0.0002598382,0.0000219732],"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":[0.0006391125,0.00009091069,0.1325002,0.0002674625,0.0002168393,0.0001854638,0.0004208461,0.002965067,0.794027,0.0001951454,0.000353689,0.06813825],"study_design_scores_gemma":[0.00001297792,0.0003422096,0.1672591,0.00005898289,0.0001978871,0.0005051842,0.000201459,0.01548741,0.808156,0.0002887126,0.007426757,0.00006312752],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9514365,0.00259067,0.03964443,0.00006608494,0.0001291373,0.00008504416,0.002623576,0.0005720427,0.00285249],"genre_scores_gemma":[0.9482316,0.001325681,0.04565273,0.000108491,0.0000250845,0.00003955547,0.001188007,0.0001100509,0.003318809],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009564096,"threshold_uncertainty_score":0.01901686,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05492161015633259,"score_gpt":0.3043130653681801,"score_spread":0.2493914552118476,"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."}}