{"id":"W2055049233","doi":"10.1093/nar/gkt339","title":"Reprever: resolving low-copy duplicated sequences using template driven assembly","year":2013,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children","funders":"National Institute of Child Health and Human Development; National Human Genome Research Institute; Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Heart, Lung, and Blood Institute; National Science Foundation","keywords":"Biology; Breakpoint; Genome; Genetics; Structural variation; Sequence (biology); Gene duplication; Computational biology; Segmental duplication; Fosmid; Whole genome sequencing; DNA sequencing; Sequence assembly; Genomics; Gene; Chromosome; Gene family","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":[0.002651623,0.001807376,0.001478919,0.001372788,0.0007818331,0.00170111,0.001934571,0.001701867,0.004312063],"category_scores_gemma":[0.00659809,0.001309268,0.002261174,0.0009368641,0.0006283533,0.001218413,0.001614892,0.00190595,0.003438155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000594861,"about_ca_system_score_gemma":0.0009925299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001298568,"about_ca_topic_score_gemma":0.002622909,"domain_scores_codex":[0.9989194,0.0002332817,0.0001047436,0.000382178,0.0002734154,0.00008699892],"domain_scores_gemma":[0.9975811,0.001241031,0.0003462763,0.000430792,0.0002897507,0.0001110037],"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":[0.002135132,0.0004909611,0.0144602,0.001912651,0.001110371,0.002888832,0.001149675,0.08250862,0.6245971,0.009664266,0.01615757,0.2429246],"study_design_scores_gemma":[0.0002056541,0.0006085007,0.004082847,0.00009368479,0.0001815621,0.00156681,0.0002136613,0.6406504,0.3272926,0.008166952,0.016726,0.0002113613],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1013314,0.000421295,0.8495462,0.0001835938,0.0001481154,0.000305595,0.002572064,0.04354162,0.001950072],"genre_scores_gemma":[0.1801574,0.0002243242,0.8052438,0.0001924912,0.00002837158,0.0003248183,0.005976007,0.006395055,0.001457805],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004312063,"threshold_uncertainty_score":0.01442528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05424222804719118,"score_gpt":0.3412862480192091,"score_spread":0.2870440199720179,"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."}}