{"id":"W4375956017","doi":"10.1093/molbev/msad106","title":"CAGEE: Computational Analysis of Gene Expression Evolution","year":2023,"lang":"en","type":"article","venue":"Molecular Biology and Evolution","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Science Foundation","keywords":"Biology; Robustness (evolution); Gene; Evolutionary biology; Phylogenetic tree; Genome; Computational biology; Gene expression; Transcriptome; Genetics; Gene expression profiling; Phylogenetics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001249788,0.00008549346,0.0001282242,0.000228275,0.00009319059,0.000004039091,0.00006728656,0.0001894852,0.00001373958],"category_scores_gemma":[0.00003436132,0.00008613645,0.00008659376,0.0004564153,0.00009815615,0.000002806992,0.00006655842,0.00004017166,0.000004924662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001005111,"about_ca_system_score_gemma":0.00002434275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003085916,"about_ca_topic_score_gemma":0.000009467122,"domain_scores_codex":[0.9993248,0.00008848837,0.0001415113,0.0002441333,0.00007453127,0.0001265306],"domain_scores_gemma":[0.9996582,0.000007808564,0.00007572206,0.0001394563,0.00007941855,0.00003934334],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00004023371,0.00001030221,0.1361204,0.000006316815,0.000204163,9.20914e-7,0.00003225139,0.03193928,0.8285468,0.002717444,0.0002240627,0.0001578387],"study_design_scores_gemma":[0.0004218639,0.0001298215,0.9274913,0.000004609074,0.0002714783,0.000005096342,0.0000779808,0.005968819,0.0596432,0.0053317,0.0004853292,0.0001687728],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8094524,0.0003667657,0.1898519,0.0000447519,0.00007044686,0.0000570122,0.00006375374,0.00001312075,0.00007979606],"genre_scores_gemma":[0.9960347,0.00001973697,0.002032822,0.00003751562,0.00002528443,0.000003294946,0.001767853,0.000004386799,0.00007438665],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7913709,"threshold_uncertainty_score":0.3512543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007140811726156031,"score_gpt":0.2554499503331256,"score_spread":0.2483091386069695,"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."}}