{"id":"W6911904316","doi":"10.5281/zenodo.14183545","title":"Pose Ensemble Graph Neural Networks to Improve Docking Performances","year":2024,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"DOCK; Training set; Graph; Artificial neural network; Docking (animal); Minification; Protein Data Bank (RCSB PDB)","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001554553,0.003720523,0.001618648,0.00177605,0.000821894,0.00138663,0.004017707,0.002101221,0.01843249],"category_scores_gemma":[0.004892862,0.0008005518,0.002242511,0.002238897,0.0005074866,0.00159473,0.0016838,0.002614936,0.01094189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001953834,"about_ca_system_score_gemma":0.001506156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0238587,"about_ca_topic_score_gemma":0.03978932,"domain_scores_codex":[0.9987935,0.0003098971,0.00004229141,0.0005107176,0.0002260315,0.000117569],"domain_scores_gemma":[0.9989255,0.0003829785,0.00003876992,0.0003449766,0.0002438843,0.00006379528],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006500492,0.0004313021,0.004288975,0.0007887801,0.0004071615,0.000171957,0.00004696249,0.5527069,0.001861878,0.003347764,0.3255762,0.1097221],"study_design_scores_gemma":[0.0001844572,0.0001341108,0.001079265,0.00007437669,0.0000822259,0.00006974708,0.00003581111,0.9645627,0.003393177,0.006980841,0.0233679,0.0000353695],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.212864,0.00845271,0.2504708,0.003343011,0.002868977,0.001330264,0.3803227,0.09951149,0.04083607],"genre_scores_gemma":[0.230155,0.001142868,0.1217675,0.001005087,0.0001674433,0.0009699564,0.6231034,0.00334854,0.0183402],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0238587,"threshold_uncertainty_score":0.06166285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02375943238494362,"score_gpt":0.2583342088544061,"score_spread":0.2345747764694625,"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."}}