{"id":"W3211144100","doi":"10.5281/zenodo.1243913","title":"Virtual Chip-Seq Predictions Of Binding Of 31 Transcription Factor In Roadmap Epigenomics Project Tissues","year":2018,"lang":"en","type":"dataset","venue":"Figshare","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Epigenomics; Transcription factor; Computational biology; Computer science; Factor (programming language); Biology; Genetics; Programming language; Gene; DNA methylation; Gene expression","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":[0.0009925804,0.001913227,0.001137731,0.001359029,0.0007230982,0.001252759,0.002415724,0.001313801,0.04886188],"category_scores_gemma":[0.002446228,0.0007587029,0.001570065,0.001719145,0.0002653117,0.0006658438,0.001610789,0.001385141,0.04719537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000927967,"about_ca_system_score_gemma":0.001398975,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006191118,"about_ca_topic_score_gemma":0.01498516,"domain_scores_codex":[0.9992557,0.0001016418,0.00005027309,0.0003011301,0.0001746936,0.0001164848],"domain_scores_gemma":[0.9991099,0.0002912189,0.00006239641,0.0002791981,0.0001632855,0.00009393038],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006575016,0.000107462,0.007715601,0.001866138,0.0002973992,0.0001792265,0.0001045889,0.004576939,0.008233749,0.001565046,0.9613135,0.01338279],"study_design_scores_gemma":[0.0008884305,0.0001871158,0.03429442,0.0003372125,0.0002925082,0.0004330583,0.0001521718,0.007419077,0.02003798,0.004207477,0.9316274,0.0001231135],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00234208,0.0001242753,0.001048402,0.00005983209,0.00003750308,0.00002325729,0.9925021,0.002409004,0.001453593],"genre_scores_gemma":[0.002066023,0.00004736653,0.00111448,0.00007087608,0.000003963335,0.00007771063,0.9955584,0.0003108413,0.0007503334],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04886188,"threshold_uncertainty_score":0.1634593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04652866252451294,"score_gpt":0.3043550129299291,"score_spread":0.2578263504054161,"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."}}