{"id":"W4393595780","doi":"10.5281/zenodo.10463493","title":"Phylogenetic Augmentation Data","year":2024,"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; Biology; Evolutionary biology; Genetics","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":[0.001640716,0.003438315,0.001671069,0.002639375,0.001275518,0.002069782,0.003782973,0.003114388,0.08854084],"category_scores_gemma":[0.005623993,0.0009510081,0.001781156,0.0044318,0.000824706,0.001469402,0.002450368,0.003666031,0.1369813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001594352,"about_ca_system_score_gemma":0.002184359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0106884,"about_ca_topic_score_gemma":0.02939049,"domain_scores_codex":[0.9984238,0.0002927333,0.0001048277,0.0005654863,0.0003815894,0.0002315969],"domain_scores_gemma":[0.9979225,0.0005601364,0.0001497166,0.000723603,0.0004459353,0.0001980325],"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":[0.0001358582,0.00008528139,0.001205347,0.0006450937,0.00004551239,0.00004976517,0.00002794279,0.001287563,0.0006232832,0.001053875,0.9889137,0.005926656],"study_design_scores_gemma":[0.0003093506,0.00004775785,0.002889273,0.0002166609,0.00004344655,0.0001208786,0.00008455772,0.002040238,0.001646312,0.003535929,0.9890215,0.00004418918],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004552579,0.0001144441,0.0003817647,0.00007500084,0.00006476881,0.00002613532,0.9965484,0.001209914,0.001124393],"genre_scores_gemma":[0.0006298526,0.00004079684,0.001155043,0.00006031889,0.00000607018,0.0001002208,0.9971554,0.0001422881,0.0007098723],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.08854084,"threshold_uncertainty_score":0.2961987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04509041217331158,"score_gpt":0.2794416007330137,"score_spread":0.2343511885597021,"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."}}