{"id":"W4205239247","doi":"10.1038/s41587-021-01111-2","title":"Deep distributed computing to reconstruct extremely large lineage trees","year":2022,"lang":"en","type":"article","venue":"Nature Biotechnology","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"National Human Genome Research Institute; Japan Science and Technology Agency; Canadian Institutes of Health Research; Ministry of Education, Culture, Sports, Science and Technology; Asahi Glass Foundation; National Cancer Institute; Government of Canada; Japan Agency for Medical Research and Development; Naito Foundation","keywords":"Lineage (genetic); Phylogenetic tree; Fractal; Scalability; Tree (set theory); Phylogenetics; Sequence (biology)","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":[0.001041309,0.0005411867,0.0006902806,0.0006874353,0.0008916368,0.001181496,0.001663938,0.0008465411,0.003026363],"category_scores_gemma":[0.005292006,0.0006262198,0.0005324234,0.001332316,0.0009645302,0.001725357,0.001741783,0.00253885,0.0005822862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001154797,"about_ca_system_score_gemma":0.001170692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005269796,"about_ca_topic_score_gemma":0.009959859,"domain_scores_codex":[0.9996538,0.00009937461,0.0000210816,0.00007758264,0.0001062656,0.00004178518],"domain_scores_gemma":[0.9967302,0.002184169,0.0001033334,0.0005518387,0.0002775537,0.0001528419],"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":[0.0004231606,0.0001865623,0.003807848,0.0001688544,0.0001695533,0.0002260146,0.0003573523,0.7395362,0.008884259,0.05926767,0.01004745,0.176925],"study_design_scores_gemma":[0.00002042378,0.00000869056,0.0001683939,0.000004109282,0.000008357383,0.00001254654,0.0000253064,0.960006,0.0009336629,0.03802941,0.0007797301,0.000003291388],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1044684,0.0006432471,0.8873142,0.0006883559,0.0001534317,0.0000649623,0.0005656985,0.003265731,0.002835953],"genre_scores_gemma":[0.5514921,0.0002511395,0.4430478,0.0002218635,0.00007884712,0.0001833268,0.001321257,0.000458608,0.002945043],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005269796,"threshold_uncertainty_score":0.01047826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005528095219353552,"score_gpt":0.2303046977257994,"score_spread":0.2247766025064458,"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."}}