{"id":"W4391588840","doi":"10.5705/ss.202023.0091","title":"Functional Adaptive Double-Sparsity Estimator for Functional Linear Regression Model with Multiple Functional Covariates","year":2024,"lang":"en","type":"article","venue":"Statistica Sinica","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Innovation and Technology Commission; City University of Hong Kong","keywords":"Covariate; Estimator; Linear regression; Linear model; Econometrics; Statistics; Regression; Computer science; Mathematics","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"],"consensus_categories":[],"category_scores_codex":[0.0005325138,0.0004072496,0.0005021031,0.0001144719,0.000481216,0.00008193648,0.0001161515,0.0001697317,0.0004161214],"category_scores_gemma":[0.001445377,0.0003023006,0.0001441886,0.0002046164,0.0002888925,0.0002695158,0.00008373219,0.0004127867,0.00005224123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000139202,"about_ca_system_score_gemma":0.000512158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009098846,"about_ca_topic_score_gemma":0.00002056012,"domain_scores_codex":[0.9973647,0.00008130442,0.0005661664,0.0008639437,0.0006341687,0.000489706],"domain_scores_gemma":[0.9902045,0.008556695,0.0001516875,0.0003334291,0.0004879115,0.0002657501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004925292,0.0002366474,0.00001999072,0.0002326643,0.0002231643,0.00002179399,0.0000678013,0.01929462,0.0002482295,0.9376059,0.03356879,0.003555117],"study_design_scores_gemma":[0.001474573,0.0002448441,0.000151738,0.0001410581,0.0001834082,0.00002046502,0.00003102528,0.5526855,0.00009459908,0.4432461,0.001462059,0.0002646429],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002392907,0.00009000459,0.9936494,0.0004284683,0.0006355799,0.0007232233,0.003151693,0.0003172517,0.0007650589],"genre_scores_gemma":[0.09669868,0.000007403795,0.8995024,0.00009517986,0.0003444826,0.0003081038,0.0004324307,0.00009043848,0.002520909],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5333909,"threshold_uncertainty_score":0.9999429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2590965294916933,"score_gpt":0.4241020710222027,"score_spread":0.1650055415305093,"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."}}