{"id":"W2803559294","doi":"10.1016/j.ymeth.2018.05.008","title":"Storage, visualization, and navigation of 3D genomics data","year":2018,"lang":"en","type":"review","venue":"Methods","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Genomics; Data science; Visualization; Computer science; Field (mathematics); Big data; State (computer science); Genome; Computational biology; Biology; Data mining; Genetics","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":[0.002666938,0.00156309,0.001593663,0.00427471,0.0003916768,0.002071128,0.002997068,0.001609346,0.004100192],"category_scores_gemma":[0.003398909,0.0007459905,0.0008012822,0.004247585,0.001610416,0.003062674,0.001732069,0.002439632,0.003757271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009922236,"about_ca_system_score_gemma":0.001849136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001996756,"about_ca_topic_score_gemma":0.002318832,"domain_scores_codex":[0.9990748,0.0001671065,0.0001101401,0.0001865209,0.0004000741,0.00006126062],"domain_scores_gemma":[0.9974189,0.001598808,0.0001954733,0.0001677325,0.0005039618,0.0001152374],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004409663,0.00003642528,0.0001678628,0.009351354,0.00005440182,0.00008765841,0.00007724084,0.0003070174,0.00282989,0.007188719,0.02204372,0.9578116],"study_design_scores_gemma":[0.000008794736,0.00002288875,0.0004301359,0.002488458,0.00007037275,0.0008917248,0.0000476687,0.0003417022,0.003081899,0.005474292,0.9871047,0.00003751009],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001744003,0.9859787,0.01014494,0.0005216753,0.000600589,0.00002895431,0.0001312226,0.000152761,0.002266828],"genre_scores_gemma":[0.001081984,0.9835653,0.01183204,0.0004567379,0.0004309519,0.00005823725,0.0003622097,0.00006173369,0.002150739],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.00427471,"threshold_uncertainty_score":0.01410425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1207057118312394,"score_gpt":0.4624113083056394,"score_spread":0.3417055964744,"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."}}