{"id":"W4393505019","doi":"10.5281/zenodo.8356747","title":"Phylogenetic Augmentation Data","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Phylogenetic tree; Evolutionary biology; Phylogenetics; Biology; Geography; Genetics; Gene","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":[0.001630588,0.003438623,0.001663648,0.002588701,0.001259887,0.002056996,0.003767996,0.003101586,0.08607881],"category_scores_gemma":[0.005478235,0.0009442087,0.001798886,0.004453973,0.0008137562,0.001447964,0.002435947,0.003677034,0.1344016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001596498,"about_ca_system_score_gemma":0.002172492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0109678,"about_ca_topic_score_gemma":0.03009637,"domain_scores_codex":[0.9984404,0.0002860728,0.000104479,0.0005579399,0.0003807575,0.0002302332],"domain_scores_gemma":[0.9979326,0.0005530977,0.0001484172,0.0007287385,0.0004406793,0.000196573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001365503,0.00008502001,0.001178508,0.0006518916,0.0000457696,0.00005065745,0.00002819657,0.001286536,0.0006260308,0.00106358,0.9889517,0.00589559],"study_design_scores_gemma":[0.0003130777,0.00004720009,0.002913043,0.0002187206,0.00004341414,0.0001240735,0.0000838117,0.002073065,0.001682577,0.003546698,0.9889099,0.0000444972],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004403196,0.0001123551,0.0003851707,0.00007246425,0.00006292922,0.00002584704,0.9965689,0.001230904,0.001101203],"genre_scores_gemma":[0.0006182233,0.00004027195,0.001152604,0.00005951712,0.000005798401,0.00009886707,0.9972103,0.0001420122,0.0006723383],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08607881,"threshold_uncertainty_score":0.2879623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05968144483556574,"score_gpt":0.2850249421197071,"score_spread":0.2253434972841413,"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."}}