{"id":"W3110364255","doi":"10.1016/j.bios.2020.112836","title":"Nanomaterial-based electrochemical sensors and biosensors for the detection of pharmaceutical compounds","year":2020,"lang":"en","type":"review","venue":"Biosensors and Bioelectronics","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":390,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Nanotechnology; Biosensor; Biochemical engineering; Human health; Pharmaceutical industry; Computer science; Materials science; Pharmacology; Medicine; Engineering","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"],"consensus_categories":[],"category_scores_codex":[0.0002721609,0.0005832821,0.001110939,0.0001086386,0.0002050025,0.00005678799,0.0002073512,0.0006391898,4.830458e-7],"category_scores_gemma":[0.0001324715,0.0003861018,0.0004812218,0.0002692813,0.0005006995,0.000003446169,0.0001070707,0.0002864798,4.453835e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004397692,"about_ca_system_score_gemma":0.0001691066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004142415,"about_ca_topic_score_gemma":0.000007548085,"domain_scores_codex":[0.9978025,0.0001557936,0.0006084279,0.0007755462,0.0001635028,0.0004942457],"domain_scores_gemma":[0.9988009,0.000184137,0.0004046457,0.0003563448,0.0001182067,0.0001357346],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000254719,0.00005125474,0.000001333861,0.001924774,0.0004370613,0.000001779315,0.000004441785,1.481521e-7,0.6766903,0.00004309422,0.0001185875,0.3204725],"study_design_scores_gemma":[0.0002439959,0.0006108434,4.134094e-7,0.0001837847,0.0008278014,0.0000683104,0.000007762081,0.0002954724,0.3882904,0.000008179364,0.609138,0.0003249832],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.003714063,0.9938799,0.0009897639,0.0001950267,0.00008051334,0.0009166801,0.0001613346,0.00005427839,0.000008409658],"genre_scores_gemma":[0.07437347,0.9238205,0.001067258,0.00009492859,0.0002988603,0.00003983712,0.0002017901,0.00007083721,0.00003254872],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.6090195,"threshold_uncertainty_score":0.9998591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02209525251095874,"score_gpt":0.3200805911790551,"score_spread":0.2979853386680964,"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."}}