{"id":"W4385999578","doi":"10.1002/cjs.11794","title":"Contrast tests for groups of functional data","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Aeronautics and Space Administration; National Oceanic and Atmospheric Administration; National Science Foundation","keywords":"Contrast (vision); Functional data analysis; Test statistic; Functional principal component analysis; Analysis of variance; Mathematics; Statistics; Covariance; Computer science; Statistical hypothesis testing; Artificial intelligence","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0008379755,0.00008312245,0.0002719188,0.0001639592,0.00006939279,0.00002386534,0.000287473,0.00004456287,0.0002482907],"category_scores_gemma":[0.01431976,0.00007392355,0.00003059327,0.0001697737,0.0001245428,0.00005771075,0.00001793645,0.0001209998,0.00000617557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000380576,"about_ca_system_score_gemma":0.0009529878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001945215,"about_ca_topic_score_gemma":0.003264291,"domain_scores_codex":[0.9989378,0.00004230811,0.0005110988,0.00009477717,0.0001808914,0.0002330765],"domain_scores_gemma":[0.9944121,0.004167093,0.0002899822,0.0002220718,0.0005590179,0.0003497312],"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":[0.00001861916,0.00001250662,0.0009116869,0.0001223446,0.00005762056,0.00005726072,0.00008668775,0.000009511846,0.00009895043,0.7079296,0.2755184,0.01517683],"study_design_scores_gemma":[0.0005844735,0.0002398747,0.01799872,0.00009793423,0.0001126012,0.00005047696,0.000173713,0.0057355,0.0000368223,0.9676253,0.007223896,0.000120721],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003213127,0.00004247251,0.9833774,0.0001884395,0.0006017524,0.0001039398,0.01222248,0.000005007234,0.0002453547],"genre_scores_gemma":[0.1845053,0.00001597557,0.8147966,0.00007882085,0.0002735108,0.000002575554,0.0001272216,0.00002579597,0.0001742142],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2682945,"threshold_uncertainty_score":0.993983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.393885353112752,"score_gpt":0.386793569681691,"score_spread":0.007091783431060983,"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."}}