{"id":"W4413874206","doi":"10.1007/978-3-031-94928-9_10","title":"Ancestral Pangenomes and Their Phylogenetic Reconstruction","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Phylogenetic tree; Artificial intelligence; 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":[0.0005069374,0.0003250166,0.0004574738,0.001638969,0.0007534882,0.001714966,0.0006480042,0.0006613381,0.006576338],"category_scores_gemma":[0.001483638,0.000487341,0.0003859206,0.002912979,0.0007539575,0.002574825,0.0009946651,0.001593544,0.001303378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005557206,"about_ca_system_score_gemma":0.0002252951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005240546,"about_ca_topic_score_gemma":0.0006249546,"domain_scores_codex":[0.9998397,0.00003970871,0.0000106882,0.00006194472,0.00002522836,0.00002270874],"domain_scores_gemma":[0.9996536,0.0001391799,0.00003430716,0.00009303605,0.0000474211,0.00003243165],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001258444,0.00008063711,0.006302136,0.001066508,0.0001374592,0.0008966072,0.001673009,0.01675607,0.07640777,0.4679987,0.004549847,0.4228729],"study_design_scores_gemma":[0.00005908874,0.0002526248,0.02918275,0.0004616944,0.0002043105,0.002746606,0.001157618,0.04014412,0.02188115,0.6604928,0.2433298,0.00008743032],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3740866,0.04104092,0.4587198,0.002168633,0.0004705914,0.000164654,0.006015593,0.001880308,0.1154529],"genre_scores_gemma":[0.7494084,0.02927125,0.1833082,0.000593563,0.0002622191,0.0001933233,0.01132127,0.0006336029,0.02500824],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006576338,"threshold_uncertainty_score":0.02200001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01120834384207413,"score_gpt":0.2195679945628719,"score_spread":0.2083596507207978,"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."}}