{"id":"W2062518981","doi":"10.1016/j.tig.2008.01.002","title":"Adapting to environmental changes using specialized paralogs","year":2008,"lang":"en","type":"article","venue":"Trends in Genetics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":91,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Biology; Function (biology); Environmental change; Salinity; Gene; Ecology; Evolutionary biology; Computational biology; Genetics; Climate change","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":[0.0000671606,0.0001654337,0.0001615108,0.00009971789,0.00009512376,0.000006481114,0.0001485748,0.00008667316,0.00004125054],"category_scores_gemma":[0.000007995121,0.0001780545,0.00005057012,0.0001118592,0.0000713563,2.845666e-7,0.000187128,0.00004971633,0.000007503346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002034949,"about_ca_system_score_gemma":0.00001526209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001886108,"about_ca_topic_score_gemma":0.0001614334,"domain_scores_codex":[0.9990659,0.00003271664,0.0001746742,0.0003212135,0.0001039158,0.0003015249],"domain_scores_gemma":[0.9996103,0.000005326914,0.00004496536,0.0002541096,0.000008231218,0.00007705862],"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":[0.00004601218,0.00005875994,0.05960308,0.000002266797,0.00003229746,0.00001316798,0.0004800651,0.002519021,0.9220418,0.000006487281,0.0005728627,0.01462419],"study_design_scores_gemma":[0.002304479,0.001039586,0.5054015,0.00001901084,0.00005136626,0.0001436295,0.0005248174,0.0009415062,0.3370713,0.00007432498,0.151219,0.001209444],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965162,0.00201183,0.0001157008,0.00008163186,0.0001629511,0.00008189413,0.00002782545,0.000002770404,0.0009992099],"genre_scores_gemma":[0.989044,0.0009395844,0.008779173,0.0002257966,0.0003774874,0.00001089226,0.00002493896,0.00002601515,0.0005721635],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5849705,"threshold_uncertainty_score":0.7260852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05469172696839392,"score_gpt":0.2793935451151987,"score_spread":0.2247018181468048,"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."}}