{"id":"W2054854610","doi":"10.1155/2014/761562","title":"State Observer Design for Delayed Genetic Regulatory Networks","year":2014,"lang":"en","type":"article","venue":"Computational and Mathematical Methods in Medicine","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada; Beijing Wuzi University","keywords":"Observer (physics); Gene regulatory network; Computer science; Linear matrix inequality; State (computer science); Control theory (sociology); Genetic network; Mathematical optimization; Gene; Genetics; Biology; Mathematics; Control (management); Artificial intelligence; Gene expression; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001816653,0.0001509247,0.0003168661,0.00005803091,0.00005409543,0.000007724453,0.0001069862,0.00009313349,0.00001781947],"category_scores_gemma":[0.000463509,0.0001207375,0.00005518258,0.000112197,0.0001744618,0.000002305693,0.00005427109,0.00006406617,8.972629e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009451414,"about_ca_system_score_gemma":0.00002193097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001031985,"about_ca_topic_score_gemma":0.000001223217,"domain_scores_codex":[0.9985739,0.0003912104,0.0003903722,0.0003113168,0.0001299593,0.0002032386],"domain_scores_gemma":[0.998821,0.0006981687,0.00008899857,0.0001874789,0.00009269104,0.0001117241],"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":[0.0001912071,0.0000929709,0.0004826893,0.0001695634,0.0002100646,0.000001835803,0.0001303674,0.8591607,0.008935002,0.008069257,0.002921964,0.1196343],"study_design_scores_gemma":[0.0007837095,0.0002806594,0.005001994,0.00004166827,0.00006065394,0.00001352362,0.00001312343,0.7530228,0.0004416586,0.2392876,0.0009090896,0.0001435085],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05429319,0.001020513,0.9441125,0.0002028372,0.0000598243,0.0002459017,8.437352e-7,0.000008819798,0.00005557161],"genre_scores_gemma":[0.1478317,0.00004026447,0.8512388,0.0004270016,0.0002269349,0.00004859625,0.00002696134,0.00002002059,0.000139732],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2312184,"threshold_uncertainty_score":0.4923531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0400740962968691,"score_gpt":0.3536375812136368,"score_spread":0.3135634849167677,"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."}}