{"id":"W4213344728","doi":"10.1021/acs.analchem.1c05107","title":"Noise-Reduced Quantitative Fluorine NMR Spectroscopy Reveals the Presence of Additional Per- and Polyfluorinated Alkyl Substances in Environmental and Biological Samples When Compared with Routine Mass Spectrometry Methods","year":2022,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Per- and polyfluoroalkyl substances research","field":"Environmental Science","cited_by":53,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chemistry; Mass spectrometry; Alkyl; Nuclear magnetic resonance spectroscopy; Analytical Chemistry (journal); Fluorine; Spectroscopy; Chromatography; Organic chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000579995,0.0002165385,0.0003613922,0.00003649381,0.0002111031,0.00002782789,0.0003596956,0.00005526372,0.02343557],"category_scores_gemma":[0.0001124558,0.0001520914,0.00004832374,0.0003325896,0.001408024,0.0001072986,0.0003382142,0.0004560806,0.000004527344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001928007,"about_ca_system_score_gemma":0.00002131278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001287978,"about_ca_topic_score_gemma":0.00001996799,"domain_scores_codex":[0.9978904,0.0002532322,0.0003247593,0.0005426125,0.0005602181,0.0004287988],"domain_scores_gemma":[0.9985849,0.0008949217,0.0001107448,0.0002440563,0.000006991899,0.0001583695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004107395,0.0001569001,0.1812161,0.0000154676,0.00004550195,0.00001747617,0.0003085174,0.00008570629,0.8166636,0.0001316343,0.0004934466,0.0004548391],"study_design_scores_gemma":[0.001901994,0.000766464,0.710124,0.00004385221,0.00006378786,0.0001200106,0.00585064,0.009686672,0.2639198,0.003561645,0.003232554,0.000728616],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.994146,0.002705685,0.0001826347,0.0004799154,0.000008673004,0.0001786718,0.0006614209,0.00001237426,0.001624616],"genre_scores_gemma":[0.9835324,0.0002250167,0.01560862,0.00003557888,0.00002179608,0.00005518946,0.000152123,0.00001068358,0.0003586095],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5527439,"threshold_uncertainty_score":0.9774572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03425545236657397,"score_gpt":0.3124257037546398,"score_spread":0.2781702513880659,"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."}}