{"id":"W2086229908","doi":"10.1080/10485252.2014.941364","title":"Switching nonparametric regression models","year":2014,"lang":"en","type":"article","venue":"Journal of nonparametric statistics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Frequentist inference; Mathematics; Covariate; Nonparametric statistics; Nonparametric regression; Econometrics; Sequence (biology); Regression; Regression analysis; Statistics; Bayesian probability; Bayesian inference","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":[0.009652035,0.0009214806,0.001972506,0.002577031,0.0006831592,0.002072001,0.003905456,0.002115737,0.004336776],"category_scores_gemma":[0.02777365,0.0007478858,0.002336863,0.003008551,0.001925933,0.002458323,0.002073654,0.002994743,0.0008889642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001291639,"about_ca_system_score_gemma":0.0009350877,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004572349,"about_ca_topic_score_gemma":0.003478465,"domain_scores_codex":[0.9942381,0.003567694,0.0001735227,0.001016458,0.0006635856,0.0003405515],"domain_scores_gemma":[0.9805185,0.01525079,0.001536502,0.001686671,0.0007410508,0.0002665472],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001713268,0.0001705097,0.008410793,0.0002234424,0.0004025564,0.0002613658,0.0004669486,0.5118088,0.001396155,0.3729366,0.003199443,0.1005521],"study_design_scores_gemma":[0.00001711706,0.00003659924,0.0009074745,0.00001759061,0.00002589201,0.00004652563,0.00002544619,0.8910457,0.0001697064,0.1061075,0.001577602,0.00002290075],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01284375,0.0002201618,0.9849668,0.0002829202,0.00003259289,0.00005526669,0.0002731412,0.0002759024,0.001049525],"genre_scores_gemma":[0.6042282,0.0008103919,0.3832126,0.0004684625,0.0003128105,0.0008537628,0.00191555,0.0002336122,0.007964683],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009652035,"threshold_uncertainty_score":0.05104542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02366288151772032,"score_gpt":0.2958462564397692,"score_spread":0.2721833749220489,"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."}}