{"id":"W4294704757","doi":"10.1111/anzs.12373","title":"Penalised, post‐pretest, and post‐shrinkage strategies in nonlinear growth models","year":2022,"lang":"en","type":"article","venue":"Australian & New Zealand Journal of Statistics","topic":"Grey System Theory Applications","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"","keywords":"Lasso (programming language); Shrinkage; Subspace topology; Mathematics; Estimator; Nonlinear system; Estimation; Shrinkage estimator; Statistics; Econometrics; Applied mathematics; Computer science; Mathematical analysis; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.002474655,0.0001918959,0.0004553378,0.0004822391,0.0001897164,0.0003757574,0.0007993676,0.0000536246,0.0006146062],"category_scores_gemma":[0.0005286001,0.0001575895,0.00007574856,0.000579301,0.0001112118,0.000632767,0.0001484637,0.0005193306,0.00002128767],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007031072,"about_ca_system_score_gemma":0.0005045518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004755123,"about_ca_topic_score_gemma":0.000138802,"domain_scores_codex":[0.9963993,0.0004180653,0.001316944,0.0002873338,0.00126122,0.0003171205],"domain_scores_gemma":[0.9966963,0.001138316,0.000857139,0.0003231989,0.0006619488,0.0003230895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001654765,0.001003879,0.06244718,0.0001110156,0.0002909814,0.002603915,0.02512189,0.05498586,0.009678972,0.4109981,0.4168858,0.0142176],"study_design_scores_gemma":[0.002748671,0.001452336,0.06561114,0.00006132819,0.00008662612,0.001944393,0.01722937,0.002704298,0.0001059244,0.8917772,0.01580674,0.0004720255],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9742163,0.000146448,0.01248498,0.008845759,0.000433081,0.0004419674,0.002495656,0.00001926251,0.0009165948],"genre_scores_gemma":[0.9760626,0.00002595134,0.01780939,0.0001862108,0.0001221103,0.000004840958,0.00002430023,0.00002125459,0.005743359],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.480779,"threshold_uncertainty_score":0.6729507,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05821540037106006,"score_gpt":0.3370547767390908,"score_spread":0.2788393763680307,"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."}}