{"id":"W1889881724","doi":"10.1093/bioinformatics/btv385","title":"Hyperscape: visualization for complex biological networks","year":2015,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Hospital for Sick Children","funders":"Centre National de la Recherche Scientifique; Heart and Stroke Foundation of Canada","keywords":"Visualization; Computer science; Biological network; Computational biology; Artificial intelligence; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000360082,0.0001707073,0.0001676984,0.00003603502,0.00009225105,0.00005767695,0.0002099918,0.000247802,0.000008484121],"category_scores_gemma":[0.00009040051,0.0001432923,0.00009532573,0.00009252307,0.00007350851,0.000009866975,0.0001131714,0.00005494578,0.00002427422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001980917,"about_ca_system_score_gemma":0.00006533364,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000146722,"about_ca_topic_score_gemma":0.000002988107,"domain_scores_codex":[0.9990241,0.00001704122,0.0004125293,0.0001243935,0.0001071763,0.0003147389],"domain_scores_gemma":[0.9992207,0.00001595555,0.0001591321,0.0002656842,0.0001648091,0.0001737314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000860318,0.0003034789,0.003310693,0.0002149706,0.0003523187,0.000001437269,0.001421276,0.02849043,0.005556268,0.02234879,0.8532228,0.08391717],"study_design_scores_gemma":[0.001356177,0.000622461,0.0002165174,0.000008847348,0.00001828453,0.00002119842,0.0005560552,0.6542165,0.0003903125,0.0004552814,0.3417849,0.0003534328],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01484594,0.0002954219,0.9774065,0.00009023798,0.0004524963,0.0005662659,0.00004574502,0.00004808938,0.00624931],"genre_scores_gemma":[0.8916976,0.0002296792,0.09952688,0.002973327,0.001138995,0.00008016846,0.003825445,0.00004520693,0.0004827011],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8778796,"threshold_uncertainty_score":0.5843289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05209407698517685,"score_gpt":0.2850710021989206,"score_spread":0.2329769252137438,"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."}}