{"id":"W2804209870","doi":"10.1002/cmdc.201800166","title":"Structure‐Based Design of a Eukaryote‐Selective Antiprotozoal Fluorinated Aminoglycoside","year":2018,"lang":"en","type":"article","venue":"ChemMedChem","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Japan Society for the Promotion of Science; Fonds de recherche du Québec – Nature et technologies; Ichiro Kanehara Foundation for the Promotion of Medical Sciences and Medical Care; Japan Science Society; Kurata Memorial Hitachi Science and Technology Foundation; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Medical Research Council","keywords":"Antiprotozoal; Eukaryote; Ribosome; Ribosomal RNA; Biology; Aminoglycoside; RNA; Biochemistry; Chemistry; Stereochemistry; Computational biology; Antibiotics; 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":[],"consensus_categories":[],"category_scores_codex":[0.0001860093,0.0002187372,0.0002252832,0.00005482382,0.00007382558,0.00001205203,0.0002820562,0.0002499705,0.0001134337],"category_scores_gemma":[0.0001840404,0.0002029525,0.00008910798,0.0001756172,0.0002053499,0.000004194386,0.00006384995,0.00007976132,0.00001395884],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001855222,"about_ca_system_score_gemma":0.0001463334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000111959,"about_ca_topic_score_gemma":0.000002777586,"domain_scores_codex":[0.9988002,0.00006841241,0.0002375073,0.000408039,0.0001757737,0.0003100743],"domain_scores_gemma":[0.999061,0.00002584605,0.0001474713,0.0004314298,0.0002459488,0.00008832464],"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":[0.0003658976,0.00004930152,0.000245603,0.00002539346,0.00005339194,0.000002366174,0.00003880872,0.000009603476,0.9959066,0.00004059896,0.0007615729,0.002500859],"study_design_scores_gemma":[0.0006401032,0.0007181244,0.0003572677,0.0000262077,0.00002210054,0.000009599908,0.00001601272,0.0001795703,0.9964273,0.0005341725,0.0008332586,0.0002362946],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9423564,0.0001864916,0.05540622,0.00005616555,0.0001486028,0.0007207121,0.00002519928,0.00003185576,0.001068335],"genre_scores_gemma":[0.9832082,0.000007483422,0.01600637,0.0001522449,0.000288924,0.00005906391,0.00003946224,0.00003679154,0.0002014402],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0408518,"threshold_uncertainty_score":0.8276165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01772863788062315,"score_gpt":0.2493616746258466,"score_spread":0.2316330367452235,"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."}}