{"id":"W2934066528","doi":"10.1007/978-1-4939-9045-0_28","title":"In Situ Hi-C for Plants: An Improved Method to Detect Long-Range Chromatin Interactions","year":2019,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":64,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Leibniz-Institut für Pflanzengenetik und Kulturpflanzenforschung; Institute of Genetics; Bundesministerium für Bildung und Forschung","keywords":"Chromosome conformation capture; Chromatin; Evening primrose; Chromosome; Genome; Biology; In situ; Computational biology; Genetics; DNA; Gene; Chemistry; Enhancer","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007912035,0.001772612,0.001031505,0.001296375,0.001006632,0.0008256331,0.00236607,0.001543457,0.003805685],"category_scores_gemma":[0.0005816441,0.0009911305,0.0006024681,0.0009348918,0.000652777,0.0008471971,0.0008596014,0.003910475,0.002659937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006583934,"about_ca_system_score_gemma":0.0006409474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002634186,"about_ca_topic_score_gemma":0.008216106,"domain_scores_codex":[0.9993629,0.000113701,0.00003662703,0.000198981,0.0001834834,0.000104459],"domain_scores_gemma":[0.9991078,0.0002938502,0.00009899861,0.0002479919,0.0001368815,0.000114479],"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":[0.00003559149,0.00001056153,0.00005281495,0.00005494096,0.000007827134,0.00001682341,0.00001295774,0.00002396631,0.9971921,0.00009251905,0.0001937439,0.002306264],"study_design_scores_gemma":[0.00001486004,0.00004562068,0.002424775,0.000007580524,0.00004271552,0.0003552456,0.00001375624,0.001472727,0.9877082,0.0001519112,0.007738678,0.00002392981],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08707824,0.00478862,0.8941775,0.0005689404,0.0003486349,0.0004353683,0.002926012,0.005446592,0.004230176],"genre_scores_gemma":[0.2200225,0.005150205,0.7461804,0.0008503129,0.0001515701,0.001299229,0.009028877,0.00207343,0.01524352],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003805685,"threshold_uncertainty_score":0.01273131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01269329020584888,"score_gpt":0.3763129242358487,"score_spread":0.3636196340299998,"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."}}