{"id":"W2990407838","doi":"10.1111/dar.13004","title":"Assessing the limit of detection of Fourier‐transform infrared spectroscopy and immunoassay strips for fentanyl in a real‐world setting","year":2019,"lang":"en","type":"article","venue":"Drug and Alcohol Review","topic":"Forensic Toxicology and Drug Analysis","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":112,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada; University of British Columbia; Institute of Indigenous Peoples' Health; Vancouver Coastal Health; British Columbia Centre on Substance Use","funders":"Health Canada; Canada Research Chairs; Michael Smith Health Research BC","keywords":"Fentanyl; Fourier transform infrared spectroscopy; Detection limit; Context (archaeology); Immunoassay; Chromatography; Point of care; Chemistry; Materials science; Analytical Chemistry (journal); Medicine; Anesthesia; Physics; Optics","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":[0.008127395,0.0009842142,0.0006093584,0.001629153,0.000480979,0.001688114,0.001635336,0.003416032,0.001003478],"category_scores_gemma":[0.01904546,0.0005720107,0.0006219338,0.0007705681,0.00155159,0.0008357327,0.0008864377,0.0007743565,0.0005684727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005658516,"about_ca_system_score_gemma":0.0006011706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001626963,"about_ca_topic_score_gemma":0.001531023,"domain_scores_codex":[0.9810411,0.005952392,0.001001729,0.002319942,0.009170267,0.0005145015],"domain_scores_gemma":[0.9811025,0.009138672,0.005388673,0.0006687321,0.00343591,0.0002654768],"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":[0.00176227,0.001097932,0.423428,0.00145806,0.0005284936,0.0005556596,0.001429986,0.001959805,0.5102934,0.0005632657,0.001162194,0.05576093],"study_design_scores_gemma":[0.0001295582,0.01187786,0.4405886,0.0007455367,0.000641652,0.008202556,0.002736149,0.01774653,0.5079368,0.001405844,0.007767574,0.0002213724],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9423399,0.006019904,0.04580634,0.00082693,0.0001780519,0.0003231291,0.0007365365,0.0002786716,0.003490482],"genre_scores_gemma":[0.9412802,0.001390693,0.05478928,0.0007755806,0.00008595548,0.0002280061,0.0005147556,0.00002792592,0.000907615],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008127395,"threshold_uncertainty_score":0.04298228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06510648991759403,"score_gpt":0.4340986612788215,"score_spread":0.3689921713612275,"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."}}