{"id":"W4388223685","doi":"10.1186/s12863-023-01166-x","title":"3-D chromatin conformation, accessibility, and gene expression profiling of triple-negative breast cancer","year":2023,"lang":"en","type":"article","venue":"BMC Genomic Data","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto; Ontario Institute for Cancer Research","funders":"Uppsala Multidisciplinary Center for Advanced Computational Science; Instituto de Salud Carlos III; Govern de les Illes Balears; Science for Life Laboratory; Fundación Francisco Cobos; Vetenskapsrådet; Knut och Alice Wallenbergs Stiftelse; European Commission","keywords":"Triple-negative breast cancer; Chromatin; Epigenetics; Breast cancer; Computational biology; Biology; CRISPR; Gene expression profiling; Cancer research; Gene expression; Profiling (computer programming); Gene; Cancer; Genetics; Computer science","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":[0.00009269094,0.0001035907,0.0001237391,0.0003936154,0.0001677122,0.0002387028,0.0001155106,0.0001875827,0.00127386],"category_scores_gemma":[0.0001086858,0.0001124982,0.0001736756,0.0004249112,0.0001076668,0.00006658159,0.000122708,0.0002099123,0.0002746457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001734191,"about_ca_system_score_gemma":0.0001137829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002095963,"about_ca_topic_score_gemma":0.004103661,"domain_scores_codex":[0.9999437,0.000004571053,0.000002968549,0.00002038213,0.00001804447,0.00001031651],"domain_scores_gemma":[0.9999343,0.00001638466,0.00001555723,0.000008160348,0.00001399028,0.00001162557],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001468549,0.00001643979,0.008751618,0.00009815941,0.00002780626,0.00007612672,0.00009827949,0.0009557783,0.9854267,0.0001138302,0.000321786,0.00396671],"study_design_scores_gemma":[0.00001581573,0.000133096,0.450717,0.00002050171,0.00008283363,0.0009950323,0.0003217997,0.0139086,0.5239961,0.0003811199,0.009388421,0.00003977901],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9820094,0.0009492773,0.007375631,0.00008897506,0.0000156997,0.00001371872,0.007656171,0.0002214153,0.001669657],"genre_scores_gemma":[0.9839613,0.0006547837,0.00657725,0.00007651107,0.000007415194,0.00003267309,0.007250603,0.00005184631,0.001387576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002095963,"threshold_uncertainty_score":0.004261494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02987020813088768,"score_gpt":0.2971238100062424,"score_spread":0.2672536018753547,"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."}}