{"id":"W1968372036","doi":"10.1081/sac-120028440","title":"Testing for No Effect in Functional Linear Regression Models, Some Computational Approaches","year":2004,"lang":"en","type":"article","venue":"Communications in Statistics - Simulation and Computation","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Test statistic; Mathematics; Linear regression; Covariance; Covariate; Resampling; Functional data analysis; Linear model; Statistics; Proper linear model; Permutation (music); Regression analysis; Statistic; Statistical hypothesis testing; Bayesian multivariate linear regression","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":[0.0008189857,0.000182793,0.0002799852,0.0002296779,0.0002338747,0.00005353355,0.0001581648,0.0001005842,0.000004084557],"category_scores_gemma":[0.003102794,0.0001802553,0.00002628314,0.0003158709,0.00013705,0.0002131376,0.000104169,0.0002326737,0.000004117772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00013994,"about_ca_system_score_gemma":0.00009046025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002819058,"about_ca_topic_score_gemma":0.00002234076,"domain_scores_codex":[0.9983866,0.0002799467,0.0006463549,0.0002832249,0.0002180194,0.0001858465],"domain_scores_gemma":[0.9870673,0.01207573,0.0002143155,0.0002769088,0.0003077294,0.00005797584],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004079648,0.0001160453,0.0005072052,0.00007365747,0.000004678596,3.633206e-7,0.0001892533,0.5528037,0.000005915411,0.4223567,0.00001508547,0.02388659],"study_design_scores_gemma":[0.0009473723,0.00008019958,0.005587712,0.00009297607,0.000009093889,7.469067e-7,0.0000244997,0.5082538,0.000001856746,0.4849012,0.000006338542,0.0000942681],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02103635,0.00008959258,0.9774979,0.0001601328,0.00007633566,0.0006777363,0.0001049636,0.00005271786,0.0003042157],"genre_scores_gemma":[0.4784816,0.000004419916,0.5211335,0.00003495892,0.00002086133,0.00007338668,0.0002324102,0.00001343043,0.000005438786],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4574452,"threshold_uncertainty_score":0.7350599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4933858251782051,"score_gpt":0.4891668984006866,"score_spread":0.00421892677751845,"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."}}