{"id":"W4375853858","doi":"10.1139/cjc-2023-0028","title":"A beginner's guide to <sup>19</sup>F NMR and its role in drug screening","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Chemistry","topic":"Chemical Synthesis and Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Chemistry; Drug discovery; Ligand (biochemistry); Drug; The Renaissance; Combinatorial chemistry; Computational biology; Mechanism of action; Chemical shift; Nanotechnology; Stereochemistry; Biochemistry; Pharmacology; In vitro; Receptor","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002769688,0.000121172,0.0001960806,0.00009448833,0.00005514354,0.00003893277,0.0002249747,0.0001046379,0.00008353701],"category_scores_gemma":[0.0004414634,0.0001214218,0.0001041036,0.0002562093,0.00003128329,0.000005183857,0.00004255991,0.0001380249,0.000005197632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000414725,"about_ca_system_score_gemma":0.0003072078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000874294,"about_ca_topic_score_gemma":0.001647889,"domain_scores_codex":[0.9990884,0.00001539311,0.0002877992,0.0001917158,0.0001074183,0.0003092661],"domain_scores_gemma":[0.9989125,0.00001806132,0.00007841814,0.0001380071,0.00008224008,0.0007707659],"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":[0.00001846818,0.000007425556,0.005769075,0.00003087485,0.00007081462,0.0001333537,0.0001759601,0.001889614,0.9637256,0.00000297032,0.02503542,0.003140404],"study_design_scores_gemma":[0.0004559722,0.0000209355,0.0008663555,0.0001275263,0.00002964366,0.0001157521,0.001044319,0.0005345266,0.7385002,0.00005388382,0.2579664,0.0002843912],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957467,0.001358178,0.00002610613,0.001295058,0.000008583637,0.00002794455,0.0000231387,0.00000290421,0.001511337],"genre_scores_gemma":[0.9969326,0.00008709289,0.0001321926,0.0002874994,0.0002810474,0.000002630332,0.00001991457,0.00001629755,0.002240674],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.232931,"threshold_uncertainty_score":0.4951437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006017052324865851,"score_gpt":0.2210893813114672,"score_spread":0.2150723289866014,"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."}}