{"id":"W3115793130","doi":"10.21203/rs.3.rs-129173/v1","title":"Applying an inverse homeostasis perspective to simplify the design and implemention of robustly-nearly-homeostatic biological networks","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Homeostasis; Perspective (graphical); Computer science; Biology; Cell biology; Artificial intelligence","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":[0.002415659,0.0003167122,0.0004398976,0.0001645865,0.0002987869,0.0001269288,0.0006407072,0.0004153978,0.00004035323],"category_scores_gemma":[0.0005274616,0.0002445038,0.0002184896,0.000588135,0.000315644,0.00000534761,0.002106018,0.0007157307,0.000005558676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001123613,"about_ca_system_score_gemma":0.0002716123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002450953,"about_ca_topic_score_gemma":0.0001424564,"domain_scores_codex":[0.9954339,0.001938615,0.0003913669,0.001073847,0.0005426607,0.0006196182],"domain_scores_gemma":[0.9976248,0.0002158053,0.0001593358,0.0009148766,0.0007398404,0.0003453685],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002818394,0.0005675569,0.02440451,0.0009529459,0.003451944,0.00005920773,0.004427994,0.7685242,0.1101655,0.001311459,0.02949861,0.05381768],"study_design_scores_gemma":[0.006871305,0.03128069,0.1639253,0.00213491,0.002002055,0.00007643695,0.1429836,0.5088865,0.06466772,0.03031773,0.0394948,0.007358957],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8750961,0.006578424,0.111634,0.001469535,0.00007874737,0.00491692,0.0001464346,0.00003445034,0.00004535652],"genre_scores_gemma":[0.9920925,0.002152247,0.004121161,0.0001295103,0.0003825545,0.0006620364,0.00039735,0.00004746412,0.00001518474],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2596377,"threshold_uncertainty_score":0.9970575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1114419468973504,"score_gpt":0.3926577078495491,"score_spread":0.2812157609521987,"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."}}