{"id":"W1974818776","doi":"10.1007/s13253-011-0066-6","title":"Estimating Parameters in Delay Differential Equation Models","year":2011,"lang":"en","type":"article","venue":"Journal of Agricultural Biological and Environmental Statistics","topic":"Mathematical and Theoretical Epidemiology and Ecology Models","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"Division of Mathematical Sciences; Natural Sciences and Engineering Research Council of Canada","keywords":"Nonparametric statistics; Semiparametric regression; Function (biology); Applied mathematics; Semiparametric model; Estimating equations; Econometrics; Likelihood function; Mathematics; Population; Computer science; Mathematical optimization; Statistics; Estimation theory; Maximum likelihood","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":[0.008715574,0.001287431,0.001993899,0.00172955,0.0005406291,0.002038445,0.002361606,0.002655167,0.001411282],"category_scores_gemma":[0.07976888,0.002153609,0.0009825971,0.001447984,0.001700322,0.003952127,0.00219045,0.002631897,0.0002703845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001578024,"about_ca_system_score_gemma":0.001410809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01235628,"about_ca_topic_score_gemma":0.0044072,"domain_scores_codex":[0.9977584,0.001283168,0.0001437322,0.0004569643,0.0001879925,0.0001697454],"domain_scores_gemma":[0.8995288,0.09504206,0.002614056,0.001280628,0.001072103,0.0004623418],"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":[0.0001088463,0.00003889298,0.004764453,0.00006981388,0.00009283177,0.00007252728,0.0001083588,0.9557164,0.0004180935,0.02495794,0.000268105,0.01338374],"study_design_scores_gemma":[0.00002064215,0.0000182283,0.0003800113,0.00001189094,0.00002143511,0.00002028329,0.00001883962,0.9676958,0.000243831,0.03137575,0.0001771704,0.00001597299],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06897572,0.0003900121,0.9293798,0.0004621155,0.00002360626,0.00004697826,0.0001800329,0.0001856016,0.0003561253],"genre_scores_gemma":[0.8645971,0.0009617505,0.1302068,0.000154657,0.0000950703,0.0002159101,0.0008298068,0.0001379639,0.002800929],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01235628,"threshold_uncertainty_score":0.04609287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06871374052468777,"score_gpt":0.245797224662299,"score_spread":0.1770834841376112,"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."}}