{"id":"W2949076105","doi":"10.1101/294405","title":"Accurate prediction of orthologs in the presence of divergence after duplication","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Gene duplication; Phylogenetic tree; Phylogenetics; Gene; Biology; Computational biology; Similarity (geometry); Function (biology); Divergence (linguistics); Evolutionary biology; Computer science; Genetics; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003214112,0.0006842705,0.001685356,0.002964005,0.001042932,0.001770269,0.001605364,0.001837971,0.002720356],"category_scores_gemma":[0.02049766,0.0005438607,0.00102736,0.002544852,0.001049201,0.003925028,0.002772073,0.002059279,0.001785811],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007812704,"about_ca_system_score_gemma":0.0009782088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0027055,"about_ca_topic_score_gemma":0.003094625,"domain_scores_codex":[0.9977586,0.0006704369,0.0001204174,0.0007039476,0.0005426594,0.0002039704],"domain_scores_gemma":[0.9910077,0.005456734,0.0008728633,0.001193372,0.0009820786,0.0004872182],"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":[0.001988775,0.0003922349,0.4414475,0.002027103,0.0006478459,0.002251331,0.0009159836,0.252772,0.04955082,0.02304397,0.02451329,0.2004491],"study_design_scores_gemma":[0.0001181445,0.0002243002,0.04723902,0.0001210198,0.0001209093,0.001221273,0.0004316842,0.8659348,0.01421562,0.05780495,0.01247885,0.00008951178],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6823017,0.003238959,0.2926799,0.001237327,0.0002081675,0.00009754662,0.00733252,0.006616557,0.006287371],"genre_scores_gemma":[0.9358326,0.0003081785,0.05373286,0.0002505471,0.0000645026,0.00004735978,0.008671771,0.0003901655,0.0007020665],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003214112,"threshold_uncertainty_score":0.01699799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01401826295538425,"score_gpt":0.2247653844295437,"score_spread":0.2107471214741595,"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."}}