{"id":"W2590738066","doi":"10.1107/s2059798316020234","title":"The<i>XChemExplorer</i>graphical workflow tool for routine or large-scale protein–ligand structure determination","year":2017,"lang":"en","type":"article","venue":"Acta Crystallographica Section D Structural Biology","topic":"Enzyme Structure and Function","field":"Materials Science","cited_by":112,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministero dello Sviluppo Economico; Ontario Ministry of Economic Development and Innovation; Canadian Institutes of Health Research; Genome Canada; Wellcome Trust; GlaxoSmithKline; Pfizer; Eli Lilly and Company","keywords":"Workflow; Computer science; Metadata; Context (archaeology); Software; Graphical user interface; Interface (matter); Identification (biology); User interface; Data mining; Database; Operating system","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":[0.006098596,0.003149257,0.002212791,0.004089691,0.001119995,0.003026384,0.005576825,0.002002711,0.1530722],"category_scores_gemma":[0.008922466,0.00202625,0.001787966,0.002939486,0.001044089,0.003039832,0.004164885,0.003484336,0.06739224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001498044,"about_ca_system_score_gemma":0.002877381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004055987,"about_ca_topic_score_gemma":0.005559687,"domain_scores_codex":[0.9975917,0.0004171555,0.0002114074,0.0004487056,0.001016167,0.0003147633],"domain_scores_gemma":[0.9963965,0.001365332,0.000285156,0.0008334668,0.0007282256,0.0003913655],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007022806,0.00008688799,0.0008761044,0.001220195,0.0001120712,0.0004587848,0.0002975701,0.0009229155,0.02512227,0.005096217,0.8734512,0.09165349],"study_design_scores_gemma":[0.001097535,0.0002629454,0.004647587,0.0005538827,0.00007617226,0.001265441,0.0001025535,0.03285988,0.07819616,0.01105294,0.8693907,0.0004941019],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.002957746,0.0006342887,0.3070095,0.001032233,0.0005183439,0.0007496972,0.06320231,0.609502,0.01439398],"genre_scores_gemma":[0.02536795,0.001403582,0.6424814,0.002020002,0.0002973973,0.003618152,0.1615012,0.1364661,0.0268441],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.1530722,"threshold_uncertainty_score":0.5120775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01219739776067173,"score_gpt":0.2657531300408534,"score_spread":0.2535557322801816,"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."}}