{"id":"W2562995081","doi":"10.1186/s12859-016-1340-y","title":"Compromise or optimize? The breakpoint anti-median","year":2016,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Genome Rearrangement Algorithms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Genome; Compromise; Phylogenetic tree; Generality; Biology; Adjacency list; Computational biology; Computer science; Data mining; Mathematics; Algorithm; Genetics; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002485907,0.0001653609,0.0001373762,0.00003387681,0.00009671807,0.00004174119,0.0003665053,0.0001065457,0.000119479],"category_scores_gemma":[0.00009932909,0.00007556289,0.00009393335,0.000079089,0.0001425513,0.000008804212,0.0001855238,0.00005074243,0.0002739503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001602282,"about_ca_system_score_gemma":0.00009010013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003298857,"about_ca_topic_score_gemma":0.00001753502,"domain_scores_codex":[0.9990479,0.00002901309,0.0003141177,0.0001367841,0.0001740068,0.0002982039],"domain_scores_gemma":[0.9991205,0.00003517389,0.0001242745,0.0005643858,0.0000595735,0.00009610613],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001598131,0.0009486799,0.03286858,0.00133091,0.001385138,0.00003354259,0.003912799,0.002528728,0.3094802,0.0007779693,0.2482603,0.396875],"study_design_scores_gemma":[0.0159276,0.001921635,0.02421796,0.0003142274,0.0002611524,0.0005020534,0.00307692,0.09601589,0.1355433,0.0003193346,0.719231,0.00266891],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3122618,0.0004737456,0.6667306,0.004341786,0.001292285,0.002244415,0.0002612306,0.00015992,0.01223413],"genre_scores_gemma":[0.3700041,0.001677438,0.6083492,0.002110572,0.001363159,0.0001720359,0.0002653959,0.0001299916,0.01592812],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4709707,"threshold_uncertainty_score":0.3521169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02001011848846677,"score_gpt":0.2385707755167301,"score_spread":0.2185606570282633,"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."}}