{"id":"W1582408600","doi":"10.1186/1471-2105-16-s4-s3","title":"The relative vertex clustering value - a new criterion for the fast discovery of functional modules in protein interaction networks","year":2015,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; National Institute for Health and Care Research; Menzies Centre for Australian Studies, King's College London, University of London; Maudsley Charity","keywords":"Cluster analysis; Computer science; Hierarchical clustering; Data mining; Node (physics); Vertex (graph theory); Modular design; Similarity (geometry); Gene ontology; False positive paradox; Theoretical computer science; Computational biology; Artificial intelligence; Biology; Gene; Graph; Engineering","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":[0.003206399,0.0008993894,0.0012404,0.008266089,0.001104632,0.002175476,0.002105038,0.001821839,0.001445708],"category_scores_gemma":[0.01471221,0.0003280572,0.001213202,0.003822722,0.001483059,0.002106261,0.001358106,0.001114246,0.0006957531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001694719,"about_ca_system_score_gemma":0.001248172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002021458,"about_ca_topic_score_gemma":0.001782817,"domain_scores_codex":[0.9960697,0.0008159668,0.0003529639,0.0007501577,0.001782919,0.0002283242],"domain_scores_gemma":[0.9914331,0.00409556,0.001377339,0.0006089029,0.00211019,0.0003747725],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001282179,0.0003065229,0.07130759,0.001518924,0.0007747706,0.0007434728,0.0007993455,0.2659307,0.06093922,0.05090785,0.01297313,0.5325163],"study_design_scores_gemma":[0.00006405302,0.0003188866,0.01374494,0.0001340376,0.0001311175,0.001004747,0.0002136726,0.9207544,0.02836861,0.02881315,0.006326924,0.0001254049],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08132721,0.00150136,0.9117365,0.0003104445,0.0001269612,0.0002893875,0.0008277363,0.001318122,0.002562235],"genre_scores_gemma":[0.4881762,0.0004581355,0.5078912,0.0001098411,0.000133197,0.000356575,0.001425892,0.0002651376,0.001183707],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008266089,"threshold_uncertainty_score":0.01695728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02733965688756511,"score_gpt":0.2520429527433197,"score_spread":0.2247032958557546,"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."}}