{"id":"W4312018781","doi":"10.1093/bioinformatics/btac813","title":"Integrative chromatin domain annotation through graph embedding of Hi-C data","year":2022,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Compute Canada","keywords":"Annotation; Chromatin; Computational biology; Genome; Embedding; Domain (mathematical analysis); Pairwise comparison; Epigenomics; Genomics; Computer science; Graph; Biology; Genetics; Theoretical computer science; Artificial intelligence; Gene; DNA methylation; Gene expression; Mathematics","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":[0.0002952884,0.0001402205,0.0001605947,0.00004761855,0.0001658862,0.00002069574,0.0005711141,0.00005561522,0.00003740428],"category_scores_gemma":[0.00003620857,0.0001338588,0.00006050573,0.0001642216,0.00006856642,0.00001807727,0.0007372899,0.0001022525,0.000003730725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000026915,"about_ca_system_score_gemma":0.00008321652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001177714,"about_ca_topic_score_gemma":0.000008151129,"domain_scores_codex":[0.998972,0.00004547259,0.0004473729,0.0001634966,0.0002015586,0.0001701119],"domain_scores_gemma":[0.9988797,0.00001486457,0.0003327459,0.0006821297,0.00006001442,0.00003049436],"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":[0.0004520522,0.001048199,0.002089111,0.00105125,0.001047211,0.00001273466,0.04168734,0.0401509,0.7092856,0.02352477,0.1484698,0.03118107],"study_design_scores_gemma":[0.005024401,0.002922331,0.001509311,0.0001365005,0.0001494273,0.0002437203,0.08237776,0.5329017,0.0694377,0.01194056,0.2912113,0.002145276],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9262607,0.0003591612,0.06845138,0.00008053944,0.0002431413,0.0002988281,0.0009936428,0.00001725671,0.003295392],"genre_scores_gemma":[0.8246561,0.0001831547,0.1710104,0.0002154273,0.00005672737,0.0000255115,0.003722162,0.00002319385,0.0001072894],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6398479,"threshold_uncertainty_score":0.5458605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01531051330598558,"score_gpt":0.267753883033361,"score_spread":0.2524433697273754,"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."}}