{"id":"W2903973767","doi":"10.1002/cpbi.69","title":"Using OmicsNet for Network Integration and 3D Visualization","year":2018,"lang":"en","type":"article","venue":"Current Protocols in Bioinformatics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Ste. Anne's Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Genome Canada","keywords":"Visualization; Computer science; Computer graphics (images); Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003048064,0.002474633,0.001438887,0.007879256,0.001425831,0.005575593,0.002026672,0.001433968,0.03257314],"category_scores_gemma":[0.007213202,0.001254434,0.002339436,0.005820873,0.0006380505,0.005459275,0.005027746,0.002532246,0.01143723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001497097,"about_ca_system_score_gemma":0.002557187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005665047,"about_ca_topic_score_gemma":0.006053843,"domain_scores_codex":[0.9981683,0.0003615814,0.0002506288,0.0003657804,0.0007247085,0.0001290639],"domain_scores_gemma":[0.9979424,0.0007144869,0.0002199842,0.0005153185,0.0004089873,0.0001988294],"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":[0.000962234,0.0002652167,0.006752488,0.004100824,0.0008606922,0.001971731,0.002417663,0.030321,0.04226695,0.1047936,0.5084789,0.2968087],"study_design_scores_gemma":[0.000192441,0.00007272952,0.004085601,0.0007184378,0.0001854472,0.0008878142,0.0004390432,0.151811,0.0321904,0.1074675,0.70169,0.0002596353],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007119991,0.001483047,0.6253926,0.001736559,0.0009568331,0.0004177719,0.06849299,0.271647,0.02275321],"genre_scores_gemma":[0.06003764,0.002936822,0.7643976,0.001046114,0.0003196727,0.001984775,0.1282933,0.03152558,0.009458464],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03257314,"threshold_uncertainty_score":0.108968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05443163514785006,"score_gpt":0.3731338653118793,"score_spread":0.3187022301640292,"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."}}