{"id":"W3190126839","doi":"10.1371/journal.pbio.3001365","title":"PhyloFisher: A phylogenomic package for resolving eukaryotic relationships","year":2021,"lang":"en","type":"article","venue":"PLoS Biology","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":141,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Ostravská Univerzita v Ostravě; Science for Life Laboratory; Dalhousie University; Deutsche Forschungsgemeinschaft; Grantová Agentura České Republiky; Division of Environmental Biology; Ministerstvo Školství, Mládeže a Tělovýchovy; US-UK Fulbright Commission; European Research Council; National Science Foundation","keywords":"Biology; Phylogenomics; Evolutionary biology; R package; Computational biology; Phylogenetics; Genetics; Clade; Gene; Computer science; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001674618,0.0001693292,0.0002181427,0.00003275057,0.0002189154,0.00001729988,0.0001674438,0.0002024586,0.00002101705],"category_scores_gemma":[0.0004588933,0.0001696074,0.0001366259,0.00007387867,0.00009149924,5.817838e-7,0.0001693708,0.00009924055,0.00001813755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001554687,"about_ca_system_score_gemma":0.00009716257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004005435,"about_ca_topic_score_gemma":0.00006043301,"domain_scores_codex":[0.9987608,0.000129516,0.0002372478,0.0004979427,0.0000365502,0.0003379118],"domain_scores_gemma":[0.9991892,0.00009678648,0.00007851628,0.0004203306,0.0001497073,0.00006544511],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003638408,0.00006031164,0.04456815,0.00002034034,0.0001757296,0.000002032391,0.00006253226,0.000008609447,0.9523586,0.0009717657,0.001106732,0.0006288009],"study_design_scores_gemma":[0.001731198,0.0007285057,0.07398664,0.00002102896,0.0001650202,0.00004911755,0.0003681946,0.0001393932,0.800293,0.008203338,0.1135726,0.000741946],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9893177,0.005527036,0.001741172,0.000458,0.0002723108,0.0002627243,0.0001318526,0.000009383957,0.002279882],"genre_scores_gemma":[0.9927179,0.0004145932,0.004858517,0.0003915307,0.0004683868,0.00009380067,0.0002941144,0.00003311932,0.0007280686],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1520656,"threshold_uncertainty_score":0.6916389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03947841470871749,"score_gpt":0.252415528739575,"score_spread":0.2129371140308575,"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."}}