{"id":"W4319299128","doi":"10.1101/2023.02.05.525388","title":"Noise properties of adaptation-conferring biochemical control modules","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Connaught Fund; University of Toronto","keywords":"Robustness (evolution); Limit (mathematics); Adaptation (eye); Noise (video); Control theory (sociology); Synthetic biology; Computer science; Control (management); Biological system; Physics; Mathematics; Biology; Bioinformatics; Artificial intelligence; Mathematical analysis","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":[0.0006463228,0.0003502744,0.0003630996,0.0005453421,0.0003060872,0.0007890772,0.0005624756,0.000574667,0.0007732051],"category_scores_gemma":[0.003513777,0.0002291542,0.0003417053,0.0001865515,0.0009790116,0.0007545135,0.0007645076,0.0004867674,0.0001048987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006939899,"about_ca_system_score_gemma":0.0002865673,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004415266,"about_ca_topic_score_gemma":0.0002505771,"domain_scores_codex":[0.9994802,0.0001090333,0.00002551326,0.0001268041,0.0001802352,0.00007827745],"domain_scores_gemma":[0.9989668,0.0004096425,0.0002381451,0.000120043,0.000120588,0.0001447404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004200239,0.0001444114,0.004180669,0.000105151,0.0000832457,0.0004460496,0.0002273996,0.401675,0.4062121,0.1695263,0.0003784448,0.01660116],"study_design_scores_gemma":[0.0000186928,0.0001103989,0.001664279,0.000006107953,0.00001401506,0.0001277161,0.00001809968,0.9347647,0.03291257,0.02990443,0.0004332162,0.00002571054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.802288,0.0001234166,0.1938202,0.0001577255,0.0000243215,0.00002381337,0.00004605675,0.0003193614,0.00319714],"genre_scores_gemma":[0.9946805,0.00002707205,0.004746665,0.00002335177,0.000007130722,0.00001864898,0.00002531081,0.00002279878,0.0004485357],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007890772,"threshold_uncertainty_score":0.005035281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01891146443429217,"score_gpt":0.2070882139133386,"score_spread":0.1881767494790464,"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."}}