{"id":"W3208749720","doi":"10.1021/acschembio.1c00657","title":"Fragment-Based Phenotypic Lead Discovery To Identify New Drug Seeds That Target Infectious Diseases","year":2021,"lang":"en","type":"article","venue":"ACS Chemical Biology","topic":"Click Chemistry and Applications","field":"Chemistry","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; Armand Frappier Museum; Institut National de la Recherche Scientifique","funders":"Mitacs; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Québec Consortium for Drug Discovery; Institut Pasteur; Institut national de la recherche scientifique","keywords":"Drug discovery; Phenotypic screening; Biology; Computational biology; Phenotype; Small molecule; Genetics; Bioinformatics; Gene","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00003256155,0.0002540927,0.0003146941,0.00002177861,0.00009553546,0.00006729299,0.0003439586,0.0002371215,0.00137892],"category_scores_gemma":[0.0002632006,0.0002543852,0.0001638474,0.0002314473,0.000119479,0.00007474822,0.0002459613,0.0002832431,0.0001769208],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009935896,"about_ca_system_score_gemma":0.0001764097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003845863,"about_ca_topic_score_gemma":0.000006203078,"domain_scores_codex":[0.9985395,0.00001777313,0.0002712281,0.0006390075,0.0001184519,0.0004140135],"domain_scores_gemma":[0.9986413,0.0003076133,0.00008643921,0.0006242666,0.00005297643,0.0002873835],"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":[0.00002905819,0.0002278544,0.01787958,0.00006335538,0.00005052113,0.000007477822,0.00002873127,0.00001181927,0.9711794,0.0002937315,0.008846076,0.001382355],"study_design_scores_gemma":[0.0006033849,0.000004766129,0.0002669921,0.00002900054,0.0000511953,0.000007950246,0.00005653699,0.00001086,0.9631679,0.003560893,0.03194585,0.0002946556],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991859,0.000523962,0.00109686,0.002843723,0.00009760425,0.00006613179,0.0002551845,0.0001882042,0.003069286],"genre_scores_gemma":[0.9921847,0.00002317522,0.0003030165,0.001337049,0.0005266265,0.00008703692,0.001786649,0.00002708724,0.003724661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02309978,"threshold_uncertainty_score":0.9999908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01384356729208004,"score_gpt":0.2829068484564612,"score_spread":0.2690632811643812,"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."}}