{"id":"W4385219658","doi":"10.1021/acs.jmedchem.3c00775","title":"<i>In Silico</i> Discovery and Subsequent Characterization of Potent 4R-Tauopathy Positron Emission Tomography Radiotracers","year":2023,"lang":"en","type":"article","venue":"Journal of Medicinal Chemistry","topic":"Medical Imaging Techniques and Applications","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Neurological Disorders and Stroke; National Institute on Aging; Ontario Research Foundation; Canada Foundation for Innovation; Azrieli Foundation; Canada Research Chairs","keywords":"Tauopathy; Positron emission tomography; Chemistry; In silico; Characterization (materials science); Computational biology; Neuroscience; Biochemistry; Nanotechnology; Pathology","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":[0.0004545206,0.0007612061,0.0006776888,0.0005719472,0.0002277569,0.0006364323,0.000579987,0.0003687675,0.002496809],"category_scores_gemma":[0.0004176097,0.0002488362,0.0007421764,0.0004649794,0.0002100356,0.0002505601,0.0002700918,0.0003521805,0.00118227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004900867,"about_ca_system_score_gemma":0.0004668492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000997475,"about_ca_topic_score_gemma":0.001689498,"domain_scores_codex":[0.9998134,0.00003945739,0.00001177959,0.00003003335,0.00005353268,0.00005183125],"domain_scores_gemma":[0.9998814,0.00002377432,0.00002850457,0.00001274996,0.00003570331,0.00001788525],"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":[0.0007160777,0.0002050074,0.001332726,0.0002323694,0.00006726683,0.0005569721,0.00004738124,0.005039363,0.974755,0.0008340419,0.00173324,0.01448056],"study_design_scores_gemma":[0.00012191,0.001469968,0.00166157,0.00001291976,0.0001197546,0.0008059227,0.00003676243,0.0107113,0.9752932,0.0001993927,0.009536321,0.0000309162],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9156483,0.003899429,0.05504677,0.001291621,0.00008755159,0.001142335,0.008058699,0.00120217,0.01362305],"genre_scores_gemma":[0.9373996,0.003918897,0.03967895,0.0004264542,0.0000428865,0.0003512113,0.01064233,0.0001707324,0.007368985],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002496809,"threshold_uncertainty_score":0.008352637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009225546854729552,"score_gpt":0.2748628281223551,"score_spread":0.2656372812676256,"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."}}