{"id":"W4379768536","doi":"10.1186/s12859-023-05340-x","title":"Rescuing biologically relevant consensus regions across replicated samples","year":2023,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada; Université Laval","keywords":"Computer science; Bioconductor; Computational biology; Scripting language; R package; Data mining; Biology; Genetics; Gene","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":[0.0004241726,0.0001921034,0.0001935922,0.00004690472,0.0002303037,0.00006406805,0.0003122552,0.0002455837,0.000005467733],"category_scores_gemma":[0.0003986215,0.0001640577,0.0001274022,0.0002654174,0.0001594398,0.000002919536,0.0003396862,0.0001099038,0.0001395846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001871656,"about_ca_system_score_gemma":0.00008814299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009550349,"about_ca_topic_score_gemma":0.00006229024,"domain_scores_codex":[0.9986109,0.00003321489,0.0005134722,0.0002499605,0.0001222216,0.0004702208],"domain_scores_gemma":[0.9988288,0.0000605879,0.0001968298,0.0007018902,0.0001034165,0.0001084572],"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":[0.0006951103,0.0003959664,0.04005339,0.001415964,0.0007166868,0.00005854287,0.004127769,0.02667215,0.6966326,0.02624165,0.1797572,0.02323297],"study_design_scores_gemma":[0.0036307,0.00129225,0.05639368,0.0001973128,0.00009803267,0.0004605796,0.01008453,0.589908,0.02543093,0.006226934,0.3037276,0.002549459],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9817936,0.0000920219,0.0151225,0.0002656668,0.0001696402,0.0002928544,0.0002431146,0.0001775121,0.001843059],"genre_scores_gemma":[0.8143108,0.001058728,0.1789064,0.0007158546,0.0002424807,0.0000618885,0.002606394,0.00007377548,0.002023614],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6712017,"threshold_uncertainty_score":0.669008,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03774352314496041,"score_gpt":0.2834220550438373,"score_spread":0.2456785318988769,"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."}}