{"id":"W2005181142","doi":"10.1080/10406630490468450","title":"DEVELOPMENT OF AN ISOTOPE-DILUTION GAS CHROMATOGRAPHIC-MASS SPECTROMETRIC METHOD FOR THE ANALYSIS OF POLYCYCLIC AROMATIC COMPOUNDS IN ENVIRONMENTAL MATRICES","year":2004,"lang":"en","type":"article","venue":"Polycyclic aromatic compounds","topic":"Analytical Chemistry and Chromatography","field":"Chemistry","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Environment; Ministry of the Environment, Conservation and Parks","funders":"","keywords":"Isotope dilution; Chemistry; Analyte; Sample preparation; Chromatography; Calibration; Gas chromatography; Extraction (chemistry); Gas chromatography–mass spectrometry; Calibration curve; Mass spectrometry; Analytical Chemistry (journal); Dilution; Environmental chemistry; Isotope analysis; Detection limit","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":[0.0009255746,0.0005841351,0.001393871,0.00138545,0.0003137391,0.00007493079,0.001205314,0.0002881206,0.0001182793],"category_scores_gemma":[0.00007236534,0.0004918799,0.0008512484,0.003942016,0.0004265189,0.0002227469,0.0001317542,0.0003320833,0.000005117004],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003017619,"about_ca_system_score_gemma":0.0001230678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003362083,"about_ca_topic_score_gemma":0.000151639,"domain_scores_codex":[0.9953942,0.00008392236,0.002023885,0.0006880934,0.001085107,0.0007248117],"domain_scores_gemma":[0.9965854,0.001032478,0.001048262,0.001084164,0.000007656774,0.0002420667],"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":[0.0002434578,0.003265144,0.02395167,0.0008624571,0.006409569,0.00001355887,0.003505839,0.0006319364,0.9549685,0.0003181472,0.00002505579,0.005804738],"study_design_scores_gemma":[0.008515308,0.0003421389,0.1319282,0.0008228308,0.009023452,0.0001192583,0.01228556,0.1135339,0.7013952,0.01881557,0.0008455247,0.002373077],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9822484,0.0009537859,0.01523888,0.0001506605,0.00004408407,0.0003407918,0.00004710236,0.00008832374,0.0008880279],"genre_scores_gemma":[0.9510339,0.0001035998,0.04828517,0.00002920901,0.00005359893,0.0001354201,0.0002801011,0.00005065885,0.00002832514],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2535732,"threshold_uncertainty_score":0.9997533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01284006792860609,"score_gpt":0.264074214670578,"score_spread":0.2512341467419719,"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."}}