{"id":"W2950655801","doi":"10.1093/bioinformatics/bty717","title":"C3D: a tool to predict 3D genomic interactions between cis-regulatory elements","year":2018,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; Ontario Institute for Cancer Research; University of Waterloo; University Health Network","funders":"Canadian Institutes of Health Research","keywords":"Chromatin; Source code; Computational biology; Computer science; Promoter; License; MIT License; Genome; DNA; R package; Gene; Biology; Data mining; Genetics; Programming language; Gene expression; Operating system","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":[0.0001661875,0.0001756002,0.0001461269,0.00007607508,0.0001433245,0.00005839515,0.0002973624,0.0001034987,0.00006148815],"category_scores_gemma":[0.00003924734,0.0001756026,0.00007462518,0.0000869162,0.00006120532,0.00001004871,0.0002823312,0.00007159697,0.0003493692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005479818,"about_ca_system_score_gemma":0.00009089876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004666572,"about_ca_topic_score_gemma":0.00002570916,"domain_scores_codex":[0.9988893,0.00001212049,0.0004878889,0.0001695506,0.0001393194,0.0003018097],"domain_scores_gemma":[0.9990996,0.000006873755,0.0001484807,0.0005101408,0.0001048167,0.0001300532],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003231929,0.0003811228,0.07682914,0.0003971809,0.001413633,0.000003962426,0.004137812,0.0006023718,0.5231549,0.0006614995,0.1471549,0.2449403],"study_design_scores_gemma":[0.001779518,0.002070365,0.09860539,0.00008504808,0.0001628301,0.00004250435,0.0006645728,0.03308195,0.03424163,0.0001828421,0.8277334,0.001349914],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.979199,0.00001576954,0.01623201,0.00005518335,0.0003359715,0.0002993391,0.0001716536,0.00002586462,0.003665216],"genre_scores_gemma":[0.9409947,0.00001558609,0.05642482,0.0005780924,0.0007343335,0.00002282732,0.0003560228,0.00002979113,0.0008437755],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6805785,"threshold_uncertainty_score":0.7160867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008380410046805961,"score_gpt":0.2422155484755282,"score_spread":0.2338351384287222,"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."}}