{"id":"W1974786680","doi":"10.5539/ijsp.v2n2p102","title":"A Note on Bivariate Smoothing for Two-Dimensional Functional Data","year":2013,"lang":"en","type":"article","venue":"International Journal of Statistics and Probability","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bivariate analysis; Smoothing; Functional data analysis; Pointwise; Mathematics; Covariate; Scalar (mathematics); Econometrics; Computer science; Statistics; Mathematical optimization","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":[0.001309571,0.000120275,0.000224513,0.0000678249,0.00006824473,0.0001128831,0.0003220615,0.00004186148,0.0003948022],"category_scores_gemma":[0.007955547,0.00009040141,0.00003908668,0.00003288521,0.00009654785,0.0001696235,0.0001310315,0.0002003944,0.000005546668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005396911,"about_ca_system_score_gemma":0.0001189459,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004039225,"about_ca_topic_score_gemma":0.000006797004,"domain_scores_codex":[0.9984597,0.00009075044,0.0006068341,0.0002100229,0.0004987411,0.0001339258],"domain_scores_gemma":[0.9926957,0.005326287,0.0003681358,0.0001985644,0.001300368,0.0001109162],"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":[0.0003166165,0.0002627525,0.0004002693,0.00005689368,0.0001378854,0.000007932997,0.00008134325,0.0001160191,0.0004017957,0.8852958,0.01132431,0.1015984],"study_design_scores_gemma":[0.0008704076,0.0002107419,0.005390577,0.00006576831,0.00003502319,0.0000375102,0.000005958724,0.03480116,0.00005762318,0.9577469,0.0006798444,0.0000984859],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02521265,0.00001608358,0.9704571,0.001510079,0.000944695,0.0002452576,0.0013884,0.000007479759,0.0002182382],"genre_scores_gemma":[0.1563729,0.000003831952,0.8429332,0.0002928808,0.0003080759,0.000008604512,0.00003564314,0.00001031546,0.00003453448],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1311602,"threshold_uncertainty_score":0.9524108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1376528070461629,"score_gpt":0.4043658020071461,"score_spread":0.2667129949609832,"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."}}