{"id":"W2949023387","doi":"10.1093/bioinformatics/btz456","title":"eFORGE v2.0: updated analysis of cell type-specific signal in epigenomic data","year":2019,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":153,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Wellcome Trust; Wellcome","keywords":"Epigenomics; Computer science; SIGNAL (programming language); Type (biology); Programming language; Biology; Genetics; DNA methylation","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":[0.008047514,0.002166187,0.001499593,0.003921818,0.0009994635,0.002560463,0.002995931,0.001251089,0.0566029],"category_scores_gemma":[0.01914953,0.00206256,0.002259335,0.00278232,0.0005448047,0.00230658,0.003220238,0.002256769,0.02656814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008136209,"about_ca_system_score_gemma":0.002057834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003620643,"about_ca_topic_score_gemma":0.007948849,"domain_scores_codex":[0.9973301,0.0006476787,0.0002873687,0.0007954923,0.0006593919,0.0002800006],"domain_scores_gemma":[0.995018,0.002908035,0.0003016954,0.001018883,0.0005474482,0.0002060025],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002398934,0.0001649627,0.02354348,0.002445082,0.001099491,0.0009011783,0.0009332913,0.0106107,0.04501934,0.008884274,0.7472547,0.1567445],"study_design_scores_gemma":[0.0007705486,0.0002118708,0.03347816,0.0006597292,0.0006820495,0.002433661,0.0001848234,0.07907575,0.06983434,0.02254975,0.789422,0.0006972121],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.01474706,0.0007771074,0.3042792,0.0006217828,0.0004773523,0.0003831078,0.3247668,0.3472877,0.006659976],"genre_scores_gemma":[0.04240848,0.0004691196,0.4426588,0.0008851578,0.0001706392,0.001627542,0.4110806,0.09050931,0.01019047],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.0566029,"threshold_uncertainty_score":0.1893556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01163571734315533,"score_gpt":0.2229129476363164,"score_spread":0.2112772302931611,"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."}}