{"id":"W3127513279","doi":"10.1093/bioinformatics/btab076","title":"WgLink: reconstructing whole-genome viral haplotypes using L0+L1-regularization","year":2021,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; Alberta Children's Hospital","funders":"Canada Foundation for Innovation","keywords":"Haplotype; Regularization (linguistics); Computational biology; Genome; Genetics; Computer science; Biology; Virology; Artificial intelligence; Gene; Genotype","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002029008,0.001574289,0.0009061793,0.001094325,0.0005934463,0.001717767,0.002660296,0.001961999,0.006622535],"category_scores_gemma":[0.006003223,0.000809221,0.001392802,0.001049225,0.0007095943,0.001385043,0.002305074,0.001972134,0.003635539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005077079,"about_ca_system_score_gemma":0.001180084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005566791,"about_ca_topic_score_gemma":0.008338834,"domain_scores_codex":[0.999396,0.0001791865,0.00002565466,0.0001924215,0.0001604034,0.00004650357],"domain_scores_gemma":[0.9988255,0.0006201002,0.00007832875,0.0002582581,0.00012975,0.00008795222],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005968881,0.0002473133,0.007957974,0.0008616137,0.0007141717,0.000429205,0.0003454309,0.5938129,0.02496354,0.01335904,0.0779371,0.2787749],"study_design_scores_gemma":[0.00005205883,0.00002631978,0.0004373681,0.00001863048,0.00001423917,0.00004117603,0.00002542413,0.9870585,0.003210843,0.005019153,0.004077956,0.00001838975],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02532684,0.0004158788,0.9347478,0.0003545833,0.0001504829,0.0001058744,0.003496073,0.03351444,0.001888022],"genre_scores_gemma":[0.1572028,0.0002685293,0.8027682,0.0005315416,0.0001179494,0.0003668336,0.0221346,0.011278,0.005331568],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006622535,"threshold_uncertainty_score":0.02215457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01705181949001315,"score_gpt":0.2314050820654523,"score_spread":0.2143532625754391,"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."}}