{"id":"W2593366388","doi":"10.1107/s2059798317003412","title":"Proper modelling of ligand binding requires an ensemble of bound and unbound states","year":2017,"lang":"en","type":"article","venue":"Acta Crystallographica Section D Structural Biology","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ontario Ministry of Economic Development and Innovation; Ministero dello Sviluppo Economico; Diamond Light Source; Engineering and Physical Sciences Research Council; Genome Canada; UCB Pharma; Wellcome Trust; GlaxoSmithKline; Pfizer; Eli Lilly and Company","keywords":"Overfitting; A priori and a posteriori; Occupancy; Statistical physics; Residual; Computer science; Ground state; Set (abstract data type); Algorithm; Mathematics; Physics; Artificial intelligence; Quantum mechanics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001041464,0.0006340233,0.001503594,0.0003773292,0.0007800793,0.001754386,0.001783694,0.001248901,0.002220103],"category_scores_gemma":[0.002068071,0.0005711488,0.001224232,0.0006767823,0.0007445797,0.002577323,0.0007499483,0.002133853,0.0008729185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001013646,"about_ca_system_score_gemma":0.001896014,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008314717,"about_ca_topic_score_gemma":0.008161531,"domain_scores_codex":[0.9995884,0.0001112463,0.00003168931,0.00009272945,0.0001254097,0.00005052013],"domain_scores_gemma":[0.9993094,0.0003451546,0.00004391523,0.0001705606,0.00008691668,0.0000439252],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008018013,0.00006748342,0.002380213,0.0001363917,0.00005183858,0.0001051988,0.0002140428,0.924755,0.01201647,0.04072158,0.0007379045,0.01873359],"study_design_scores_gemma":[0.000007611166,0.00004747005,0.0003395269,0.00001800664,0.00001463766,0.00003350866,0.0000463221,0.9783196,0.002248591,0.01659448,0.002309892,0.00002041034],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.128373,0.0005977713,0.8628582,0.0005366577,0.00006601909,0.00007124831,0.0006548593,0.000693438,0.00614891],"genre_scores_gemma":[0.7016266,0.002330434,0.2867891,0.0003096001,0.00005933731,0.0006779695,0.002429175,0.0004896515,0.005288135],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008314717,"threshold_uncertainty_score":0.01653266,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02806243079111027,"score_gpt":0.287329022108017,"score_spread":0.2592665913169068,"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."}}