{"id":"W2536804470","doi":"10.5539/ijsp.v5n6p32","title":"Linear Hybrid Deterministic Dynamic Modeling for Time-to-Event Processes: State and Parameter Estimations","year":2016,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Gene Regulatory Network Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Mathematical Sciences","keywords":"Discrete time and continuous time; Computer science; Discretization; Event (particle physics); Process (computing); Discrete event dynamic system; Mathematical optimization; Hazard; Estimation theory; Scope (computer science); Mathematics; Discrete system; Algorithm; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.002769619,0.0009535985,0.0009658769,0.0007446166,0.0003272899,0.001661607,0.001874601,0.001362456,0.002971914],"category_scores_gemma":[0.008214991,0.0005827409,0.001019963,0.0007505711,0.001246123,0.001835404,0.001435866,0.001901911,0.0003778347],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001235293,"about_ca_system_score_gemma":0.0009724374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005920423,"about_ca_topic_score_gemma":0.003419516,"domain_scores_codex":[0.9987112,0.0005566613,0.00006403874,0.0003393502,0.0002356924,0.00009294834],"domain_scores_gemma":[0.9952391,0.003577418,0.0005973267,0.0002253801,0.0002910394,0.0000696523],"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":[0.000025421,0.000019786,0.0006316567,0.00005874522,0.00003231013,0.0000502176,0.00007180591,0.912691,0.0003830896,0.07865149,0.0001885715,0.007195899],"study_design_scores_gemma":[0.000001949137,0.000006284982,0.00004502475,0.000003949685,0.00000481708,0.000005787171,0.000004814118,0.9926958,0.00007455936,0.00692815,0.0002245292,0.000004298909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00352061,0.000086667,0.9954881,0.00009097205,0.00001605033,0.00001515946,0.00004225739,0.00005367587,0.0006865248],"genre_scores_gemma":[0.8265987,0.0007988662,0.1621401,0.0001820645,0.0001208638,0.0004836204,0.0003854574,0.00006973826,0.009220591],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005920423,"threshold_uncertainty_score":0.01464731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01029771019972561,"score_gpt":0.2818029173542002,"score_spread":0.2715052071544746,"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."}}