{"id":"W2965995818","doi":"10.1186/s13015-019-0150-y","title":"A cubic algorithm for the generalized rank median of three genomes","year":2019,"lang":"en","type":"article","venue":"Algorithms for Molecular Biology","topic":"Genome Rearrangement Algorithms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Fundação de Amparo à Pesquisa do Estado de São Paulo; Genome Canada; Alfred P. Sloan Foundation","keywords":"Genome; Linear subspace; Heuristics; Time complexity; Combinatorics; Rank (graph theory); Matrix (chemical analysis); Computer science; Algorithm; Omega; Polynomial; Upper and lower bounds; Mathematics; Mathematical optimization; Biology; Pure mathematics; Physics; Genetics","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":[0.0009039096,0.00100039,0.001369833,0.001677924,0.001371796,0.001820279,0.001769919,0.001240149,0.0168876],"category_scores_gemma":[0.003617077,0.000562627,0.001710743,0.001953102,0.000961147,0.001961991,0.003026481,0.002081935,0.003133769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001725457,"about_ca_system_score_gemma":0.003200216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007175635,"about_ca_topic_score_gemma":0.01021602,"domain_scores_codex":[0.9989582,0.0001532359,0.00006668293,0.0003664523,0.0002600244,0.0001952804],"domain_scores_gemma":[0.9989483,0.0004126733,0.00009825412,0.0002720015,0.0001811274,0.00008767426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006379602,0.0003160801,0.001709594,0.0003810621,0.0001183758,0.0002132914,0.0004896207,0.1655527,0.01581626,0.06490953,0.01809351,0.7317622],"study_design_scores_gemma":[0.0003291902,0.000270795,0.0007748917,0.00003911078,0.00004311596,0.0002321915,0.0003624547,0.8292009,0.01001794,0.1419152,0.01674238,0.00007181091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02571553,0.0001589679,0.9614118,0.0003421012,0.00005452918,0.0001949937,0.0005397375,0.005821044,0.005761399],"genre_scores_gemma":[0.09747425,0.00006545561,0.8968763,0.0000958886,0.00002625983,0.0001825483,0.00129638,0.0005691306,0.003413758],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0168876,"threshold_uncertainty_score":0.05649465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01477803924146979,"score_gpt":0.2761304000805498,"score_spread":0.26135236083908,"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."}}