{"id":"W4206675874","doi":"10.1002/0470011815.b2a09034","title":"Nonlinear Regression","year":2005,"lang":"en","type":"other","venue":"Encyclopedia of Biostatistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Nonlinear system; Estimator; Nonlinear regression; Applied mathematics; Mathematics; Linear model; Variance (accounting); Regression analysis; Function (biology); Mathematical optimization; Computer science; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001720061,0.0003861458,0.0007534546,0.0001762211,0.00002889435,0.000006419495,0.0002405406,0.0003668082,0.003668298],"category_scores_gemma":[0.001909547,0.0003145801,0.00008860185,0.0001186454,0.0001704444,0.00002086679,0.00009082078,0.0002951139,0.00006491099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002679283,"about_ca_system_score_gemma":0.00008152064,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000233844,"about_ca_topic_score_gemma":0.00004509688,"domain_scores_codex":[0.9982479,0.00009233628,0.0005808354,0.0003741517,0.0003967796,0.0003080365],"domain_scores_gemma":[0.9975427,0.001067544,0.0006280848,0.0005410374,0.00007544011,0.0001452258],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001198937,0.0001414934,0.00000380415,0.000451963,0.00004234854,0.00002515062,0.00006483927,4.405138e-7,0.000008890846,0.111609,0.7509688,0.1366713],"study_design_scores_gemma":[0.0002700294,0.00007857692,0.000002806028,0.0005092967,0.0001195827,0.00000339205,0.00001750795,0.0002194674,0.0000446123,0.1024357,0.8959498,0.0003492028],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"methods","genre_scores_codex":[9.097212e-7,0.0003954286,0.4704171,0.00002314192,0.0003416581,0.0002141482,0.001961768,0.0001001968,0.5265456],"genre_scores_gemma":[0.000001275935,0.002100391,0.5803899,0.00002066097,0.0004847713,0.000007015759,0.00006828405,0.000338535,0.4165892],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.1449811,"threshold_uncertainty_score":0.9999306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04575251585955533,"score_gpt":0.3973023941090751,"score_spread":0.3515498782495198,"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."}}