{"id":"W2110092182","doi":"10.1093/bioinformatics/bts349","title":"MolClass: a web portal to interrogate diverse small molecule screen datasets with different computational models","year":2012,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Institute for Research in Immunology and Cancer","funders":"Wellcome Trust","keywords":"Computer science; Software; Source code; Fingerprint (computing); Database; Web service; Python (programming language); Data mining; Cheminformatics; Function (biology); Open source; World Wide Web; Information retrieval; Bioinformatics; Programming language; Artificial intelligence; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000292574,0.0002452412,0.0002159646,0.0002113378,0.0001108281,0.0002019952,0.0007998666,0.0000449162,0.0000141279],"category_scores_gemma":[0.00002841394,0.0001962858,0.00006314792,0.0003421466,0.00004627085,0.001751697,0.0008544303,0.0001282601,0.0001165384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007471552,"about_ca_system_score_gemma":0.0001204031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000136015,"about_ca_topic_score_gemma":0.00001998672,"domain_scores_codex":[0.9983156,0.00006365338,0.0004074604,0.000198744,0.0005735152,0.0004410207],"domain_scores_gemma":[0.9987616,0.0001440983,0.0001647557,0.0004677635,0.00009911846,0.0003626783],"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":[0.00006874282,0.0004129335,0.0008393906,0.00009033597,0.0001608116,0.00002278475,0.006884948,0.8618406,0.00002069358,0.1084456,0.007207506,0.01400568],"study_design_scores_gemma":[0.0004483704,0.0001038021,0.001633751,0.00004218274,0.00001514987,0.00005353464,0.000198565,0.9956952,0.00009688303,0.001021668,0.0004006182,0.0002902604],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1204051,0.00001398502,0.8768753,0.0002073072,0.000164873,0.0002866491,0.000315656,0.0001176822,0.001613465],"genre_scores_gemma":[0.5386387,0.000001150514,0.4601887,0.000752366,0.00003831915,0.00001425744,0.0003361169,0.00001075107,0.00001971066],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4182335,"threshold_uncertainty_score":0.8004301,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04619267256830262,"score_gpt":0.2841637598046638,"score_spread":0.2379710872363612,"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."}}