{"id":"W6959056778","doi":"10.1021/ac3018229.s001","title":"Reusable Solid-Phase Microextraction\\nCoating for Direct\\nImmersion Whole-Blood Analysis and Extracted Blood Spot Sampling Coupled\\nwith Liquid Chromatography–Tandem Mass Spectrometry and Direct\\nAnalysis in Real Time–Tandem Mass Spectrometry","year":2016,"lang":"en","type":"article","venue":"Figshare","topic":"Biosimilars and Bioanalytical Methods","field":"Immunology and Microbiology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Mass spectrometry; Detection limit; Dried blood spot; Extraction (chemistry); Liquid chromatography–mass spectrometry; Analytical Chemistry (journal); Matrix (chemical analysis); Sample preparation; Coating","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006506941,0.001338004,0.00061325,0.0005335212,0.0002074908,0.0004149379,0.0007089816,0.000751783,0.001194214],"category_scores_gemma":[0.0007071446,0.0003844518,0.0005037241,0.0003082837,0.0004117941,0.0003977388,0.0004056242,0.0005808605,0.00110329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003902972,"about_ca_system_score_gemma":0.0004828148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004631348,"about_ca_topic_score_gemma":0.001526595,"domain_scores_codex":[0.9989865,0.0001105617,0.00009472673,0.0002950494,0.0004506889,0.00006251395],"domain_scores_gemma":[0.9995843,0.0001017758,0.00009728529,0.00006680864,0.0001241384,0.00002571555],"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":[0.00004746747,0.00002461477,0.0000725321,0.0000627567,0.000008476033,0.0000338711,0.000008722944,0.00003850248,0.9965114,0.00003092891,0.00003454561,0.003126113],"study_design_scores_gemma":[0.000007458867,0.0001703416,0.000728454,0.000006049431,0.000015449,0.0001739462,0.000005560542,0.0007846466,0.9968222,0.00001886587,0.001255656,0.00001124701],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6561922,0.005422149,0.3295513,0.0002675167,0.0004130581,0.001379416,0.00133247,0.001721474,0.003720513],"genre_scores_gemma":[0.5881505,0.004172433,0.3882478,0.0004393059,0.0001181834,0.001460938,0.002510672,0.00029446,0.01460564],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.001338004,"threshold_uncertainty_score":0.003995001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0270525187348146,"score_gpt":0.3163272625483348,"score_spread":0.2892747438135201,"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."}}