{"id":"W1533146036","doi":"10.1186/s12864-015-1647-5","title":"An assembly and alignment-free method of phylogeny reconstruction from next-generation sequencing data","year":2015,"lang":"en","type":"article","venue":"BMC Genomics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":186,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec en Outaouais","funders":"Institute of Botany, Chinese Academy of Sciences; Kunming Institute of Botany, Chinese Academy of Sciences; Beijing Institute of Genomics, Chinese Academy of Sciences; Chinese Academy of Sciences; National Science Foundation","keywords":"Genome; Biology; Phylogenetic tree; Phylogenomics; Alignment-free sequence analysis; Phylogenetics; Computational biology; Sequence assembly; Genomics; Whole genome sequencing; DNA sequencing; Multiple sequence alignment; Hybrid genome assembly; Evolutionary biology; Pairwise comparison; Comparative genomics; Bootstrapping (finance); Reference genome; Genetics; Sequence alignment; Computer science; Gene; Clade; Artificial intelligence","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":[0.004177576,0.001794726,0.001343936,0.003810731,0.00186709,0.001494062,0.002924702,0.00263061,0.004207797],"category_scores_gemma":[0.01411003,0.001360103,0.002898025,0.002356317,0.001084914,0.001844566,0.001917432,0.003716449,0.002404846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009264218,"about_ca_system_score_gemma":0.002251135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003074976,"about_ca_topic_score_gemma":0.003441267,"domain_scores_codex":[0.9976713,0.0008443503,0.0001432709,0.0005369533,0.000663096,0.0001410363],"domain_scores_gemma":[0.9958075,0.002107915,0.0003873727,0.0007605804,0.0007738788,0.0001627695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005214268,0.0003400994,0.008177767,0.0007169869,0.001250627,0.001023419,0.0007415105,0.3051155,0.05365365,0.03669536,0.01615864,0.575605],"study_design_scores_gemma":[0.00006711966,0.00006659212,0.001417486,0.00003841499,0.00007605198,0.0004891339,0.00004530564,0.9558572,0.007933516,0.02429685,0.009628657,0.00008372533],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003908198,0.0000983133,0.9937521,0.00006650231,0.00004855322,0.00003995258,0.0001727822,0.001703155,0.0002104266],"genre_scores_gemma":[0.02592744,0.00008766852,0.9711707,0.00008193986,0.00004789991,0.0001763976,0.001166169,0.0008642207,0.0004777074],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004207797,"threshold_uncertainty_score":0.02209336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.142870198343256,"score_gpt":0.3041024578783139,"score_spread":0.1612322595350578,"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."}}