{"id":"W4385851466","doi":"10.1021/acs.analchem.3c01462","title":"Performance Evaluation of Extraction Coatings with Different Sorbent Particles and Binder Composition","year":2023,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Coating; Sorbent; Sorption; Chemical engineering; Extraction (chemistry); Polyacrylonitrile; Particle (ecology); Chemistry; Solid-phase microextraction; Composite material; Materials science; Chromatography; Polymer; Organic chemistry; Adsorption; Gas chromatography–mass spectrometry; Mass spectrometry","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":[],"consensus_categories":[],"category_scores_codex":[0.0004823002,0.0002020775,0.0002675889,0.00002672834,0.00007840864,0.00002571525,0.0001010352,0.000136354,0.0008215177],"category_scores_gemma":[0.0001471911,0.0001675168,0.00005355186,0.0002447044,0.0001939804,0.00008087233,0.00006948256,0.0002104041,0.00001168763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001448627,"about_ca_system_score_gemma":0.00006633896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004305203,"about_ca_topic_score_gemma":4.227163e-7,"domain_scores_codex":[0.9981273,0.00002188386,0.000378566,0.0003674797,0.0008200652,0.0002846457],"domain_scores_gemma":[0.999006,0.0001965433,0.0001484166,0.0002503699,0.0002328055,0.0001658489],"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":[0.0001264079,0.0001746074,0.0406616,0.0008038781,0.0001342608,0.000006264351,0.0000996462,0.0003206592,0.9468524,0.00001631481,0.00008005725,0.01072392],"study_design_scores_gemma":[0.0006119701,0.00001262394,0.01059295,0.0001402298,0.0002571724,0.00001599496,0.0002167241,0.1778479,0.8099603,0.0001230276,0.00002120233,0.0001999312],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933588,0.00002217891,0.0004632413,0.0001637386,0.000007457576,0.00005216168,0.000007579511,0.00008817875,0.005836654],"genre_scores_gemma":[0.998834,0.00003269321,0.0005516313,0.00001117614,0.00005200234,0.00002893199,0.0001026851,0.0000195639,0.0003673722],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1775272,"threshold_uncertainty_score":0.8995043,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05255656664638983,"score_gpt":0.3276507842572393,"score_spread":0.2750942176108495,"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."}}