{"id":"W2805938851","doi":"10.1016/j.tig.2018.05.002","title":"Comparing Apples to Apples and Oranges to Oranges","year":2018,"lang":"en","type":"letter","venue":"Trends in Genetics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; McGill University and Génome Québec Innovation Centre; McGill Genome Centre","funders":"","keywords":"Biology; Genome; Evolutionary biology; Genetics; Computational biology; Genomics; Gene","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001328798,0.0004711599,0.0005122062,0.0003134795,0.00008552874,0.0000636571,0.0004397303,0.0005144061,0.00001757159],"category_scores_gemma":[0.00002107956,0.0004767828,0.00007971626,0.0002216684,0.0001312705,3.667008e-7,0.0006666894,0.000262893,0.00002310319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002144874,"about_ca_system_score_gemma":0.00002763985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004890759,"about_ca_topic_score_gemma":0.001258366,"domain_scores_codex":[0.9980111,0.00005786267,0.0003371093,0.0008482951,0.0001901225,0.0005555444],"domain_scores_gemma":[0.9990686,0.00002322897,0.0000830606,0.0006207817,0.00007963216,0.0001247117],"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":[0.00003666848,0.00002533587,0.01871157,0.00008364845,0.000142377,0.00001815529,0.0004472781,0.0001705,0.03940364,0.000004188304,0.927197,0.01375963],"study_design_scores_gemma":[0.0002993138,0.0003897166,0.02250611,0.00004159289,0.0000510373,0.00000964901,0.0000591533,0.000008953427,0.00938167,0.00003226395,0.9666091,0.0006114157],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9068038,0.01171166,0.0001637982,0.0776519,0.0006179804,0.0005037687,0.0003220874,0.00001517581,0.002209855],"genre_scores_gemma":[0.7287653,0.004030271,0.02359886,0.2240441,0.01113259,0.0003843765,0.0009453584,0.0003308273,0.006768342],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1780384,"threshold_uncertainty_score":0.9997684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03967613075610597,"score_gpt":0.2825144751703607,"score_spread":0.2428383444142547,"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."}}