{"id":"W2092376921","doi":"10.2307/3316020","title":"Model diagnostics for smoothing spline ANOVA models","year":2004,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Interpretability; Smoothing spline; Smoothing; Spline (mechanical); Statistics; Mathematics; Econometrics; Computer science; Estimation; Variance (accounting); Artificial intelligence; Spline interpolation; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007736936,0.0002126078,0.0005121015,0.0001964125,0.000192238,0.00006524821,0.000274709,0.0001072777,0.00002283428],"category_scores_gemma":[0.00679347,0.0001951686,0.0001057186,0.0001074215,0.0001270811,0.0001982022,0.00001244516,0.0003169035,0.000001655078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002841525,"about_ca_system_score_gemma":0.001706987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002026726,"about_ca_topic_score_gemma":0.003770366,"domain_scores_codex":[0.9980912,0.00003426107,0.0009350865,0.0001734153,0.0002695142,0.0004965659],"domain_scores_gemma":[0.9957746,0.001778126,0.0004710486,0.0002295481,0.0009211865,0.0008255114],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001675651,0.00002645479,0.000005807387,0.00007193381,0.00003222834,0.0001252239,0.0004959205,0.116697,0.00002178368,0.871999,0.00495776,0.005550217],"study_design_scores_gemma":[0.0008144028,0.0001593509,0.000004765345,0.0001043458,0.0001055001,0.00005658322,0.00008073109,0.1422801,0.00005925712,0.8554628,0.0006821659,0.0001900277],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001107352,0.000173905,0.9948696,0.0003697829,0.0003416271,0.0002339712,0.002584352,0.000008100666,0.0003112541],"genre_scores_gemma":[0.07870366,0.00006181365,0.9205443,0.0003151535,0.0001703085,0.000005579128,0.0000130265,0.00005859199,0.0001275618],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07759631,"threshold_uncertainty_score":0.8132908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1897151714629249,"score_gpt":0.3914770017694614,"score_spread":0.2017618303065366,"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."}}