{"id":"W4394483610","doi":"10.6084/m9.figshare.20267233","title":"Additional file 4 of Toward a base-resolution panorama of the in vivo impact of cytosine methylation on transcription factor binding","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill Genome Centre","funders":"","keywords":"Methylation; Cytosine; Panorama; In vivo; Transcription (linguistics); DNA methylation; Transcription factor; Biology; Genetics; Computational biology; Chemistry; Computer science; DNA; Gene; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001225496,0.002261825,0.001733936,0.002056762,0.000941424,0.002310858,0.002917198,0.001994345,0.4946813],"category_scores_gemma":[0.01077694,0.0007413731,0.001673651,0.003145215,0.0003683915,0.001413944,0.00126858,0.001710384,0.1674227],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001174548,"about_ca_system_score_gemma":0.00172637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01141304,"about_ca_topic_score_gemma":0.02752868,"domain_scores_codex":[0.9992725,0.0001181401,0.00006827051,0.0003049116,0.000132301,0.0001038542],"domain_scores_gemma":[0.9953297,0.003234525,0.0002360707,0.000491988,0.0004949254,0.0002127241],"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":[0.0001631051,0.00003933316,0.002046002,0.002039971,0.00008543885,0.00004520682,0.00002835964,0.0008233312,0.0002218669,0.0005215182,0.9914078,0.002578067],"study_design_scores_gemma":[0.002298897,0.00008823105,0.01232122,0.001073914,0.0002491952,0.0002553739,0.0001306578,0.002664585,0.001349519,0.007059188,0.9724225,0.0000866644],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007717211,0.00002664109,0.00007777123,0.00002317332,0.00000743726,0.000005629669,0.9993218,0.0002227755,0.0002375745],"genre_scores_gemma":[0.001099256,0.00003900186,0.000499451,0.00006630765,0.000008585992,0.00008986162,0.9972631,0.0002054542,0.0007290553],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4946813,"threshold_uncertainty_score":0.7207758,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03706312621934934,"score_gpt":0.2791796182122251,"score_spread":0.2421164919928757,"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."}}