{"id":"W2945589655","doi":"10.1021/acs.analchem.9b00983","title":"Measurement of Free Drug Concentration from Biological Tissue by Solid-Phase Microextraction: In Silico and Experimental Study","year":2019,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Analytical chemistry methods development","field":"Chemistry","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Thermo Fisher Scientific","keywords":"Chemistry; Multiphysics; Matrix (chemical analysis); Extraction (chemistry); In silico; Chromatography; Bovine serum albumin; Solid-phase microextraction; Mass spectrometry; Gas chromatography–mass spectrometry; Biochemistry; Thermodynamics; Finite element method","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003728513,0.0003144914,0.0005736965,0.00001330433,0.0000338533,0.00003422356,0.0003231133,0.0002347474,0.00401941],"category_scores_gemma":[0.0002956702,0.0003014896,0.00007635083,0.0001343512,0.0001791317,0.00007923441,0.0001898545,0.0003780953,0.00001522267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003149652,"about_ca_system_score_gemma":0.00007898766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001017227,"about_ca_topic_score_gemma":0.000003034228,"domain_scores_codex":[0.9975384,0.00004285849,0.0007519324,0.0007282409,0.0005914867,0.0003470217],"domain_scores_gemma":[0.9987953,0.0001747591,0.0001677197,0.0005304494,0.00009709619,0.0002346882],"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":[0.0001809424,0.002182832,0.02445794,0.00008365418,0.0001085204,0.00001972258,0.0001415645,0.000002050768,0.9723482,0.00000395505,0.0003138158,0.0001568653],"study_design_scores_gemma":[0.003273903,0.00006153337,0.0003763637,0.00006793112,0.00005110604,0.000004611982,0.001758183,0.0007779736,0.9927934,0.00005952228,0.0004582307,0.0003172717],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939858,0.0006628096,0.0001776146,0.0001155465,0.00002362218,0.0001508506,0.00005307305,0.00003491204,0.004795801],"genre_scores_gemma":[0.9987756,0.00001459547,0.0003714281,0.00002849158,0.00006989668,0.00002210858,0.00007538602,0.00001865575,0.0006238464],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02408158,"threshold_uncertainty_score":0.9999437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03222930773854016,"score_gpt":0.3472647263287596,"score_spread":0.3150354185902194,"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."}}