{"id":"W3142986659","doi":"10.1002/mrc.5156","title":"Detection, discrimination and quantification of amphetamine, cathinone and <i>nor</i> ‐ephedrine regioisomers using benchtop <sup>1</sup> H and <sup>19</sup> F nuclear magnetic resonance spectroscopy","year":2021,"lang":"en","type":"article","venue":"Magnetic Resonance in Chemistry","topic":"Forensic Toxicology and Drug Analysis","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Biotechnology and Biological Sciences Research Council; Natural Sciences and Engineering Research Council of Canada; Manchester Metropolitan University","keywords":"Cathinone; Chemistry; Structural isomer; Ephedrine; Designer drug; Nuclear magnetic resonance spectroscopy; Mass spectrometry; Quantitative analysis (chemistry); Analytical Chemistry (journal); Chromatography; Amphetamine; Nuclear magnetic resonance; Drug; Stereochemistry; Psychology","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":[0.0002181505,0.0003690888,0.0001530432,0.0004168063,0.0002014445,0.0002968243,0.0001805587,0.0003534693,0.0009232118],"category_scores_gemma":[0.0004842293,0.0001617787,0.000208907,0.0002424029,0.0002937697,0.0002204838,0.0002177725,0.0002140293,0.0003381167],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001946276,"about_ca_system_score_gemma":0.0002878412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001307449,"about_ca_topic_score_gemma":0.001933748,"domain_scores_codex":[0.9997682,0.00004676863,0.00001710734,0.00006242537,0.00008290431,0.00002253726],"domain_scores_gemma":[0.9997911,0.00004590841,0.0000616317,0.00001533824,0.00006116077,0.00002489032],"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":[0.00008050577,0.00001186327,0.0008060118,0.00002240016,0.000006647416,0.0000329404,0.00001757981,0.00005330813,0.9967386,0.00001668035,0.00001446391,0.002198973],"study_design_scores_gemma":[0.00000704058,0.0003925636,0.0109996,0.000007498526,0.00001921496,0.000364491,0.00005400478,0.001242947,0.9861589,0.0000235351,0.0007194584,0.00001078554],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9857978,0.000721857,0.01117685,0.00003957384,0.00001375676,0.00005148545,0.0004190553,0.00009848776,0.001681055],"genre_scores_gemma":[0.9743313,0.0009150938,0.02199317,0.00005977163,0.00001468458,0.00006883761,0.0006604173,0.00001890943,0.001937886],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001307449,"threshold_uncertainty_score":0.003088474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03244631638317894,"score_gpt":0.3252948537506754,"score_spread":0.2928485373674964,"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."}}