{"id":"W4390684801","doi":"10.1016/j.micinf.2024.105297","title":"NMR spectroscopy can help accelerate antiviral drug discovery programs","year":2024,"lang":"en","type":"review","venue":"Microbes and Infection","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Mitacs; Université de Paris; Québec Consortium for Drug Discovery; Ministère de l'Économie, de l’Innovation et des Exportations du Québec","keywords":"Drug discovery; Timeline; Workflow; Human immunodeficiency virus (HIV); Computational biology; Nuclear magnetic resonance spectroscopy; Multidisciplinary approach; Data science; Biology; Nanotechnology; Computer science; Chemistry; Bioinformatics; Virology; Materials science; Stereochemistry","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":[0.001331263,0.0009731372,0.00110239,0.003099598,0.0003616864,0.001740202,0.001074172,0.001968144,0.007199174],"category_scores_gemma":[0.001516738,0.0003684346,0.0006482787,0.002009619,0.0007981296,0.002529766,0.001147241,0.003141619,0.005611122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001173151,"about_ca_system_score_gemma":0.001212605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001221955,"about_ca_topic_score_gemma":0.001964561,"domain_scores_codex":[0.9996892,0.00006724773,0.00003028438,0.00005221619,0.0001231656,0.00003787248],"domain_scores_gemma":[0.9993319,0.0003321085,0.00005692196,0.00002613409,0.0001938281,0.00005905449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006107513,0.00009156152,0.0001279985,0.008568447,0.00006892673,0.0001759595,0.0000688427,0.0004399671,0.002125598,0.02073532,0.04461738,0.922919],"study_design_scores_gemma":[0.000008435445,0.00004242177,0.0002138599,0.001785107,0.00002700973,0.000296086,0.00002772761,0.00005271364,0.000378892,0.002897362,0.9942586,0.00001178211],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001026722,0.9941207,0.0003385243,0.0008837621,0.0004095559,0.000008800127,0.00003408345,0.00002178223,0.004080183],"genre_scores_gemma":[0.0008929825,0.9963613,0.000494389,0.0004505767,0.0002826141,0.00001117963,0.00003966881,0.000004596231,0.001462664],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.007199174,"threshold_uncertainty_score":0.02408361,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01808125722438694,"score_gpt":0.2926122264456702,"score_spread":0.2745309692212833,"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."}}