{"id":"W3041248822","doi":"10.1093/bioinformatics/btaa588","title":"TreeSAPP: the Tree-based Sensitive and Accurate Phylogenetic Profiler","year":2020,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Genome British Columbia; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; National Energy Research Scientific Computing Center; Joint Genome Institute; Compute Canada","keywords":"Python (programming language); Phylogenetic tree; Metagenomics; Computer science; Tree (set theory); Rank (graph theory); Taxonomic rank; Software; Genome; Biology; Data mining; Ecology; Gene; Genetics; Mathematics","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":[0.003112865,0.002566259,0.001885082,0.002409153,0.001357047,0.003499731,0.003079524,0.001308143,0.02370717],"category_scores_gemma":[0.009299323,0.001885357,0.001929371,0.002469014,0.0009595827,0.00389345,0.002922378,0.003685916,0.02465445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007380135,"about_ca_system_score_gemma":0.002312325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003205893,"about_ca_topic_score_gemma":0.003829463,"domain_scores_codex":[0.9975373,0.0003733592,0.0001882673,0.0007703916,0.0009095503,0.0002211295],"domain_scores_gemma":[0.9969358,0.001160304,0.0004772138,0.0004544825,0.0006938664,0.0002783444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002731597,0.0002867242,0.01282888,0.003275005,0.0008281414,0.001091106,0.00227916,0.01031078,0.07826337,0.01700596,0.6273345,0.2437646],"study_design_scores_gemma":[0.0005166865,0.0004876541,0.01519083,0.0007029111,0.0004181694,0.002064669,0.0007112589,0.2433694,0.1127063,0.04960749,0.573427,0.0007975865],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.01391862,0.0008810463,0.4119313,0.0005352306,0.0004883899,0.0004198203,0.07920962,0.4858736,0.006742339],"genre_scores_gemma":[0.07465811,0.001151583,0.6411883,0.001065002,0.0002285561,0.001724525,0.1497345,0.1205138,0.009735567],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.02370717,"threshold_uncertainty_score":0.07930845,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01811510835827763,"score_gpt":0.2240769398793476,"score_spread":0.2059618315210699,"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."}}