{"id":"W3046203440","doi":"10.3390/molecules25153448","title":"Systematic Evaluation of Different Coating Chemistries Used in Thin-Film Microextraction","year":2020,"lang":"en","type":"article","venue":"Molecules","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council; U.S. Department of Veterans Affairs","keywords":"Solid-phase microextraction; Extraction (chemistry); Graphene; Materials science; Coating; Solid phase extraction; Polyacrylonitrile; Oxide; Carbon nanotube; Divinylbenzene; Chemical engineering; Polystyrene; Chromatography; Nanotechnology; Chemistry; Gas chromatography–mass spectrometry; Mass spectrometry; Polymer; Styrene; Copolymer","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":[0.001483913,0.00166752,0.0009036121,0.001059451,0.000449899,0.0006563219,0.0005808768,0.0008616199,0.0005628381],"category_scores_gemma":[0.002543,0.0005996696,0.0006537598,0.0008702066,0.0004585764,0.0005827567,0.0005271427,0.0006745797,0.0004396401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000390958,"about_ca_system_score_gemma":0.0005483044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001037344,"about_ca_topic_score_gemma":0.002645615,"domain_scores_codex":[0.9985077,0.0002415956,0.0002043992,0.0002671164,0.0006620279,0.0001171739],"domain_scores_gemma":[0.9990262,0.0003233783,0.0001666434,0.00007342516,0.0003573728,0.00005301295],"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":[0.00004343154,0.00002456132,0.000310013,0.0003080872,0.00004078176,0.00005288954,0.0000206179,0.0001196232,0.9950327,0.00001901224,0.00002562068,0.004002789],"study_design_scores_gemma":[0.000004474711,0.0002666181,0.001708333,0.00002201717,0.00008613119,0.0001334539,0.00002316967,0.0003764891,0.9962053,0.00001312622,0.001149297,0.00001169101],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.921322,0.02419466,0.04788468,0.0002679588,0.0002669617,0.001611251,0.001029275,0.0004341435,0.00298903],"genre_scores_gemma":[0.7666547,0.04112799,0.1854578,0.0003134097,0.00009702435,0.001095605,0.0019425,0.000285134,0.003025783],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00166752,"threshold_uncertainty_score":0.007847786,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05371002283115631,"score_gpt":0.307775904186628,"score_spread":0.2540658813554717,"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."}}