{"id":"W2552320392","doi":"10.15252/msb.20167216","title":"Dynamical compensation in physiological circuits","year":2016,"lang":"en","type":"article","venue":"Molecular Systems Biology","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Azrieli Foundation","keywords":"Biology; Compensation (psychology); Computational biology; Neuroscience","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000364296,0.0004124852,0.0002312175,0.0003515712,0.0002923699,0.0007300517,0.0005733122,0.0006730022,0.002106484],"category_scores_gemma":[0.001719521,0.0001775932,0.0003683396,0.0001410433,0.001109866,0.0008284359,0.0007876524,0.0006023822,0.0002907196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006440022,"about_ca_system_score_gemma":0.0002943773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004195251,"about_ca_topic_score_gemma":0.0002536437,"domain_scores_codex":[0.9996444,0.00007084997,0.00001706399,0.0001132268,0.0001103396,0.00004416915],"domain_scores_gemma":[0.9995745,0.0001696277,0.00009565012,0.00006275263,0.00006795047,0.00002950366],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001260001,0.00005316559,0.001031792,0.0001535347,0.00004815214,0.0002036215,0.0001865293,0.2364449,0.2350294,0.4661973,0.0008633368,0.05966223],"study_design_scores_gemma":[0.00005084867,0.0002394251,0.001506088,0.00002495926,0.00003000378,0.0002588299,0.00003699153,0.7570653,0.03296639,0.198889,0.008881771,0.00005050456],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07208509,0.0004995715,0.9095012,0.0005518462,0.000126245,0.00005237504,0.00004970933,0.000527282,0.01660672],"genre_scores_gemma":[0.9530185,0.0002829201,0.042057,0.0001945561,0.00008423826,0.00009997114,0.0000434084,0.00006774818,0.004151705],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002106484,"threshold_uncertainty_score":0.007046878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01133547254958493,"score_gpt":0.2391861055719336,"score_spread":0.2278506330223487,"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."}}