{"id":"W2975248425","doi":"10.1021/acssensors.9b01616","title":"Electrochemical Aptamer-Based Sensors for Improved Therapeutic Drug Monitoring and High-Precision, Feedback-Controlled Drug Delivery","year":2019,"lang":"en","type":"article","venue":"ACS Sensors","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":274,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Allergy and Infectious Diseases; Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; W. M. Keck Foundation","keywords":"Aptamer; Therapeutic drug monitoring; Pharmacokinetics; Biomedical engineering; Vancomycin; Drug delivery; Drug; Dosing; Therapeutic index; Computer science; Pharmacology; Materials science; Medicine; Nanotechnology; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006962297,0.0005037733,0.0003983917,0.0002735237,0.0001135588,0.0006296683,0.0005629443,0.0008174446,0.0005639239],"category_scores_gemma":[0.0009704239,0.0002762732,0.0002696508,0.0002680401,0.0003116659,0.0006858687,0.00040944,0.0009890355,0.0003423899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004487008,"about_ca_system_score_gemma":0.0003077184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003894837,"about_ca_topic_score_gemma":0.0005361782,"domain_scores_codex":[0.9990552,0.0001680493,0.00008760558,0.000200242,0.0004151102,0.00007374892],"domain_scores_gemma":[0.9997203,0.00008608121,0.00007571347,0.00002193,0.00006991901,0.00002608956],"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":[0.00003599393,0.00002349427,0.00005061354,0.00005711076,0.000004116404,0.00002933369,0.00001993875,0.0003449316,0.9886366,0.0005045372,0.0001245052,0.01016894],"study_design_scores_gemma":[0.00001089616,0.0002019465,0.0002696306,0.000006364241,0.000008249192,0.0001994788,0.000008627125,0.005634796,0.9901531,0.0001546677,0.003337134,0.00001508275],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2933763,0.01770414,0.6776958,0.001378581,0.0006650203,0.000454825,0.0003498516,0.002349929,0.006025548],"genre_scores_gemma":[0.6470851,0.005607349,0.3392966,0.0009897671,0.0001548792,0.000210245,0.000213508,0.00008392723,0.006358556],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0008174446,"threshold_uncertainty_score":0.003682017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00551917795468949,"score_gpt":0.242998238783277,"score_spread":0.2374790608285875,"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."}}