{"id":"W1566143784","doi":"10.1002/jez.b.22555","title":"Molecular mechanisms of paralogous compensation and the robustness of cellular networks","year":2013,"lang":"en","type":"review","venue":"Journal of Experimental Zoology Part B Molecular and Developmental Evolution","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Institute of Genetics; Consejo Nacional de Ciencia y Tecnología; University of California Institute for Mexico and the United States","keywords":"Robustness (evolution); Biology; Gene; Gene duplication; Evolvability; Genetics; Computational biology; Phenotype; Neofunctionalization; Evolutionary biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004571092,0.0003460601,0.001061267,0.0001354005,0.00007591509,0.00001421262,0.0002235086,0.0004259183,0.00001281435],"category_scores_gemma":[0.0000453706,0.0002559217,0.0003313164,0.000120946,0.0006034318,0.00001065242,0.0002373444,0.0002196916,8.072819e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006124501,"about_ca_system_score_gemma":0.0002024955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001043512,"about_ca_topic_score_gemma":0.000001921606,"domain_scores_codex":[0.997746,0.0004236826,0.001093802,0.0002820807,0.0002361552,0.0002182908],"domain_scores_gemma":[0.9984037,0.00003656963,0.001111282,0.0001874095,0.0001612233,0.00009978537],"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":[0.001953674,0.001955161,0.0001774067,0.005436114,0.007233218,0.0001444522,0.0005847771,0.01245212,0.8331042,0.06038946,0.00140402,0.07516543],"study_design_scores_gemma":[0.05399163,0.01580722,0.0007849858,0.01809345,0.01359535,0.02934633,0.00920749,0.03651603,0.6798721,0.008533721,0.1241506,0.01010111],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.02460912,0.8479679,0.1265537,0.00001177958,0.0002856459,0.0004905536,0.000007708915,0.000002395993,0.00007118523],"genre_scores_gemma":[0.3936121,0.6015281,0.004479356,0.00004608461,0.00006700314,0.00004027458,0.0001498132,0.00004205406,0.00003524563],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.369003,"threshold_uncertainty_score":0.9999893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01253657746942338,"score_gpt":0.2579291195089586,"score_spread":0.2453925420395353,"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."}}