{"id":"W4234525228","doi":"10.32920/14650038","title":"Adaptive Methods For Stochastic Simulation Of Biochemical Systems","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Key (lock); Scale (ratio); Noise (video); Stochastic simulation; Stochastic process; Mathematical optimization; Stochastic modelling; Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001550364,0.001116609,0.001026877,0.0008917736,0.0005255821,0.0008499752,0.00144989,0.001633463,0.002088537],"category_scores_gemma":[0.006147678,0.0004758355,0.001000902,0.0009314669,0.001573854,0.0008160162,0.001548956,0.002271868,0.0005041237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001077121,"about_ca_system_score_gemma":0.001136816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004994831,"about_ca_topic_score_gemma":0.002758834,"domain_scores_codex":[0.9991933,0.0004102728,0.00003731643,0.00007990251,0.0002458178,0.00003347899],"domain_scores_gemma":[0.9975128,0.001880104,0.0001482886,0.0001367011,0.0002562688,0.00006589177],"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":[0.00002866758,0.0000201918,0.0002830334,0.0000903553,0.00003828092,0.00003931735,0.0000565056,0.9126334,0.001734667,0.06918632,0.000506431,0.01538293],"study_design_scores_gemma":[0.000005207454,0.000003907399,0.00001653524,0.00000337957,0.000001402648,0.000003313884,0.000001631738,0.9916647,0.00009882921,0.007655196,0.0005435858,0.000002269224],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004897077,0.0007183519,0.9920398,0.0002060523,0.00008986604,0.00005190403,0.00002944685,0.0001765164,0.001790992],"genre_scores_gemma":[0.3471579,0.002224639,0.6391733,0.0002275125,0.0003337025,0.001057866,0.0002380013,0.0004711824,0.009115831],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004994831,"threshold_uncertainty_score":0.009931505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03167196576424023,"score_gpt":0.3477356095726567,"score_spread":0.3160636438084165,"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."}}