{"id":"W2213699459","doi":"10.6084/m9.figshare.2059944.v1","title":"Supplementary Data for CAFA2","year":2016,"lang":"en","type":"article","venue":"Lirias","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Lawrence Berkeley National Laboratory; Natural Sciences and Engineering Research Council of Canada; Biotechnology and Biological Sciences Research Council; Office of Science; Directorate for Biological Sciences; National Institutes of Health; Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja; China Scholarship Council; Parkinson's UK; National Science Foundation; Royal Society; National Key Research and Development Program of China; British Heart Foundation; Alexander von Humboldt-Stiftung; Academy of Finland; National Natural Science Foundation of China; Microsoft Research; KU Leuven; Fundação de Amparo à Pesquisa do Estado de São Paulo; Gordon and Betty Moore Foundation; U.S. Department of Energy","keywords":"Computer science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002093281,0.002372947,0.002876784,0.006362518,0.00327788,0.003235531,0.004700391,0.002368807,0.6800386],"category_scores_gemma":[0.01165187,0.0018158,0.001633857,0.008517724,0.0006852781,0.003247257,0.002121246,0.003384517,0.4034515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002014989,"about_ca_system_score_gemma":0.003334496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01156188,"about_ca_topic_score_gemma":0.01620021,"domain_scores_codex":[0.9981503,0.0001522738,0.0002143631,0.0004654944,0.0007476994,0.00026975],"domain_scores_gemma":[0.9938331,0.002520164,0.0005133395,0.001111094,0.001249575,0.0007727391],"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":[0.0003521932,0.00008845776,0.0008578572,0.001659147,0.00006484007,0.00009748187,0.00005536168,0.0005771763,0.003718233,0.002019424,0.9794858,0.01102399],"study_design_scores_gemma":[0.000434579,0.00008790588,0.006171171,0.0003951725,0.0001133514,0.0004016552,0.00006761339,0.0009604811,0.004833293,0.007518007,0.9789176,0.00009934838],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004995733,0.0004804757,0.002664775,0.0002292763,0.0003176887,0.00006499184,0.9872154,0.002542318,0.005985477],"genre_scores_gemma":[0.002993664,0.000403946,0.005082573,0.0003628366,0.0001007017,0.0003544167,0.9813699,0.002318394,0.007013623],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6800386,"threshold_uncertainty_score":0.4563861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05467910202720348,"score_gpt":0.3136231768431366,"score_spread":0.2589440748159331,"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."}}