{"id":"W2043029113","doi":"10.1371/journal.pcbi.1002833","title":"Visual Data Mining of Biological Networks: One Size Does Not Fit All","year":2013,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Ontario Institute for Cancer Research; University Health Network","funders":"","keywords":"Workflow; Computer science; Data science; Biological network; Focus (optics); Data mining; Biological data; Scale (ratio); Bioinformatics; Database; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007577546,0.001545619,0.001466413,0.006146909,0.00120933,0.006575609,0.003243026,0.001486797,0.005999457],"category_scores_gemma":[0.03322992,0.0009400017,0.001550569,0.004157878,0.001822453,0.009695758,0.004797603,0.003431371,0.002853323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001033899,"about_ca_system_score_gemma":0.001537512,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0016786,"about_ca_topic_score_gemma":0.00309295,"domain_scores_codex":[0.9974571,0.0009545256,0.0002350593,0.0003136855,0.0009669809,0.00007265538],"domain_scores_gemma":[0.9863839,0.007683462,0.0007436883,0.002625728,0.001699427,0.0008637694],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005172649,0.0001619963,0.0066114,0.005170233,0.0009238793,0.001266128,0.005338605,0.00771834,0.01941714,0.119153,0.223697,0.610025],"study_design_scores_gemma":[0.0001327214,0.000110355,0.004276277,0.002756408,0.0002280507,0.002672883,0.002868806,0.06677309,0.01092513,0.6015539,0.3074794,0.000223133],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007277294,0.00805566,0.9382724,0.01396588,0.0008097616,0.0003169143,0.003345394,0.02034308,0.007613655],"genre_scores_gemma":[0.06497806,0.009528829,0.9063272,0.003060694,0.0005232751,0.0004415647,0.005410231,0.005809112,0.003921061],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007577546,"threshold_uncertainty_score":0.04007441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05420045082562499,"score_gpt":0.2888016699568761,"score_spread":0.2346012191312511,"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."}}