{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001743062,0.0001613951,0.0002526907,0.00002750919,0.00005006403,0.00001793848,0.0004391299,0.0002626382,0.0001550564],"category_scores_gemma":[0.0001399249,0.0001160175,0.00005669584,0.00005494248,0.0001981385,0.000007732261,0.0005302001,0.00009552661,0.00001938504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006214626,"about_ca_system_score_gemma":0.0000434484,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001356188,"about_ca_topic_score_gemma":0.00000548075,"domain_scores_codex":[0.9987917,0.00007637597,0.0004293056,0.0003505365,0.00007816427,0.0002739237],"domain_scores_gemma":[0.9990415,0.0002493521,0.0001940698,0.0003068693,0.0001317037,0.00007653376],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007873586,0.002061356,0.04303918,0.0001834132,0.003467381,0.000004784123,0.0003556601,0.05736422,0.7765196,0.007568195,0.02431407,0.08433476],"study_design_scores_gemma":[0.002158714,0.001907069,0.03152606,0.0000571985,0.0001024194,0.00002661523,0.0001944953,0.9340903,0.009711885,0.01189145,0.007285535,0.001048302],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9646909,0.0003196362,0.03350206,0.0005641963,0.000195317,0.0002873388,0.0001337939,0.00001941924,0.0002873384],"genre_scores_gemma":[0.9738772,0.00008152999,0.02195035,0.001284552,0.0003669887,0.00001698355,0.002358579,0.00001146914,0.00005236026],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.876726,"threshold_uncertainty_score":0.4731055,"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."}}