{"id":"W4386331757","doi":"10.1101/2023.08.29.555243","title":"High-resolution diploid 3D genome reconstruction using Pore-C data","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Haplotype; Ploidy; Genome; Biology; Imputation (statistics); Computational biology; Human genome; Genetics; Computer science; Allele; Gene; Missing data; Machine learning","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":[0.000642436,0.0004902633,0.0005670557,0.001377891,0.0004171595,0.0009635184,0.0007844585,0.0007357607,0.004244158],"category_scores_gemma":[0.001795045,0.0004916363,0.0007748599,0.001458431,0.0004846372,0.0006125289,0.00110321,0.001084635,0.001145129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004138535,"about_ca_system_score_gemma":0.0007287209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003420589,"about_ca_topic_score_gemma":0.00450673,"domain_scores_codex":[0.9997134,0.00005329912,0.00001464942,0.0000888248,0.00009999439,0.00002988353],"domain_scores_gemma":[0.9992064,0.0002657642,0.00007132782,0.0002640659,0.0001219373,0.00007049508],"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":[0.0009512089,0.0001968894,0.03202747,0.001448609,0.0005166353,0.002655531,0.00100429,0.2906657,0.456293,0.03929873,0.02768367,0.1472584],"study_design_scores_gemma":[0.00008025974,0.00008293184,0.01379852,0.0000728873,0.00007770209,0.001133514,0.0003978658,0.8097861,0.115102,0.02291937,0.03638494,0.0001639098],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1692118,0.0006102254,0.8055042,0.0004039512,0.0001409837,0.0000717687,0.01228586,0.008205645,0.003565481],"genre_scores_gemma":[0.4789985,0.0006034139,0.4962855,0.0001313141,0.00002292937,0.0001156724,0.0209599,0.001550524,0.00133234],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004244158,"threshold_uncertainty_score":0.01419806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03711645189609128,"score_gpt":0.2405851535054792,"score_spread":0.2034687016093879,"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."}}