{"id":"W2780817719","doi":"10.1101/222562","title":"CREAM: Clustering of genomic REgions Analysis Method","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; Ontario Institute for Cancer Research; University of Toronto","funders":"Prostate Cancer Canada; Princess Margaret Cancer Foundation; Government of Ontario; Canadian Institutes of Health Research; Cancer Research Society; Ontario Institute for Cancer Research; Terry Fox Research Institute; Movember Foundation","keywords":"CTCF; Enhancer; Computational biology; Chromatin; Biology; Cluster analysis; Gene; Genome; Transcription factor; Promoter; Cohesin; Genetics; Computer science; Gene expression; Artificial intelligence","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":[0.002348928,0.002478317,0.001978377,0.006094115,0.001208621,0.002130845,0.002958646,0.001971259,0.01264215],"category_scores_gemma":[0.007956106,0.0009810264,0.004031984,0.004056084,0.0006095928,0.001179955,0.002194438,0.002568888,0.01196825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000957761,"about_ca_system_score_gemma":0.002418329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005685214,"about_ca_topic_score_gemma":0.008862253,"domain_scores_codex":[0.9968029,0.0007610476,0.0002714458,0.001363471,0.0005873527,0.000213832],"domain_scores_gemma":[0.997943,0.0008778661,0.0001647553,0.0003657546,0.0005584147,0.000090153],"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":[0.001068036,0.0004138763,0.009093988,0.001871016,0.001519826,0.0005225852,0.0003968323,0.09890679,0.02579386,0.01042111,0.1477281,0.7022641],"study_design_scores_gemma":[0.0002833725,0.0001475775,0.005090566,0.0001430941,0.0002176562,0.0004937394,0.0002349375,0.8837441,0.01794809,0.02827737,0.0632765,0.000143056],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007356955,0.0006753565,0.936708,0.0002528115,0.0001740849,0.0005938132,0.01501467,0.03792653,0.001297732],"genre_scores_gemma":[0.03593412,0.0002306565,0.9190086,0.0002717528,0.00007143769,0.001123789,0.03700846,0.00351619,0.002835087],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01264215,"threshold_uncertainty_score":0.04229218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01337990327326306,"score_gpt":0.2496594168712122,"score_spread":0.2362795135979491,"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."}}