{"id":"W2055341260","doi":"10.1142/s0219691309002969","title":"ON WAVELET METHODS FOR TESTING EQUALITY OF MEAN RESPONSE CURVES","year":2009,"lang":"en","type":"article","venue":"International Journal of Wavelets Multiresolution and Information Processing","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland; York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wavelet; Mathematics; Thresholding; Transformation (genetics); Algorithm; Cascade algorithm; Feature (linguistics); Orthogonal wavelet; Discrete wavelet transform; Domain (mathematical analysis); Nonparametric statistics; Applied mathematics; Mathematical optimization; Computer science; Wavelet transform; Statistics; Artificial intelligence; Mathematical analysis; Image (mathematics)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03615838,0.001650311,0.001871181,0.003522059,0.0007206058,0.00140964,0.002552489,0.002452308,0.001794237],"category_scores_gemma":[0.1139984,0.0008377471,0.002265625,0.002621874,0.004480307,0.002572026,0.00296223,0.004492768,0.0007115378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007290154,"about_ca_system_score_gemma":0.001230995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009594621,"about_ca_topic_score_gemma":0.0004413059,"domain_scores_codex":[0.97474,0.01778466,0.001062528,0.001962738,0.003994255,0.0004557597],"domain_scores_gemma":[0.8600621,0.1268931,0.003934972,0.005019408,0.003680174,0.000410232],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005820671,0.0002548742,0.004716413,0.0006487768,0.0006048377,0.0004900298,0.0005403406,0.2147439,0.02248462,0.2640254,0.001490784,0.4894178],"study_design_scores_gemma":[0.0001108492,0.0005351616,0.003724621,0.0001611765,0.00008478314,0.0004663851,0.00009746556,0.7786627,0.01164385,0.2001668,0.004193123,0.0001529928],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001894885,0.0001530143,0.9975662,0.00004953895,0.00001638089,0.00003648985,0.00001794449,0.0000584522,0.0002070522],"genre_scores_gemma":[0.05940926,0.0008524596,0.93748,0.0001695984,0.0001820037,0.0007704395,0.000247031,0.0001394118,0.0007497375],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03615838,"threshold_uncertainty_score":0.1912261,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05173223996797143,"score_gpt":0.3947029306618671,"score_spread":0.3429706906938956,"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."}}