{"id":"W3088959651","doi":"10.1093/biolinnean/blaa140","title":"River capture or ancestral polymorphism: an empirical genetic test in a freshwater fish using approximate Bayesian computation","year":2020,"lang":"en","type":"article","venue":"Biological Journal of the Linnean Society","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Biology; Approximate Bayesian computation; Monophyly; Population; Ecology; Mitochondrial DNA; Evolutionary biology; Freshwater fish; Fish <Actinopterygii>; Phylogenetics; Clade; Genetics; Fishery; Gene; Demography","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":[0.01718991,0.0002895523,0.0006913366,0.001434137,0.0008588969,0.001387385,0.001419805,0.001203085,0.003167361],"category_scores_gemma":[0.08357051,0.0002595593,0.0006653404,0.001305725,0.002691091,0.001794824,0.001234412,0.001103904,0.0001296539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008608769,"about_ca_system_score_gemma":0.0008885729,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00621843,"about_ca_topic_score_gemma":0.004025431,"domain_scores_codex":[0.9908198,0.006751904,0.0003432809,0.001134082,0.0007279025,0.0002231122],"domain_scores_gemma":[0.8978828,0.09470424,0.0030843,0.001845392,0.001625783,0.0008574444],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001537257,0.0003621214,0.4833013,0.0001979884,0.0007984294,0.0007006873,0.000794118,0.3799122,0.003828616,0.06125405,0.0006718543,0.06664147],"study_design_scores_gemma":[0.00005536229,0.0001605946,0.02464947,0.00002560194,0.00004725566,0.0001734828,0.0001797992,0.9523059,0.0004732507,0.02170313,0.0001998636,0.00002626702],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8379573,0.00008902814,0.1603501,0.0002266116,0.00000780588,0.00006635283,0.0001162499,0.00006853944,0.001117996],"genre_scores_gemma":[0.9833891,0.00001276202,0.01640613,0.00002586933,0.000005429336,0.00002368232,0.00005876923,0.000005630293,0.00007261027],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01718991,"threshold_uncertainty_score":0.09091002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06124626057493238,"score_gpt":0.278778939432515,"score_spread":0.2175326788575826,"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."}}