{"id":"W1993387761","doi":"10.1002/asmb.861","title":"Robust designs for Haar wavelet approximation models","year":2010,"lang":"en","type":"article","venue":"Applied Stochastic Models in Business and Industry","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University","funders":"","keywords":"Optimal design; Mathematics; Mathematical optimization; Heteroscedasticity; Haar; Wavelet; Computer science; Applied mathematics; Algorithm; Statistics; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02282222,0.001335442,0.001637727,0.00153294,0.0004499238,0.001462448,0.002081147,0.002149191,0.003139505],"category_scores_gemma":[0.05806532,0.001245079,0.001654531,0.001099696,0.002030877,0.002501157,0.002638897,0.002216401,0.0008990557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001040744,"about_ca_system_score_gemma":0.001477154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004113945,"about_ca_topic_score_gemma":0.0003132886,"domain_scores_codex":[0.9818712,0.01270513,0.0006223461,0.001992218,0.002402578,0.0004065033],"domain_scores_gemma":[0.9749802,0.01790684,0.002594427,0.002454935,0.001802193,0.0002614078],"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":[0.0005812579,0.0001969184,0.001263011,0.0006210526,0.000305226,0.00007753165,0.0002021096,0.2906835,0.007508219,0.5334923,0.001140856,0.1639279],"study_design_scores_gemma":[0.000169988,0.0005601128,0.0005762015,0.0001015848,0.00008380329,0.00005528647,0.00003419256,0.7402207,0.005193032,0.2489222,0.004017992,0.00006489801],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002018946,0.0000967434,0.997549,0.00003156981,0.00001143374,0.00002762332,0.00002075632,0.00003616454,0.0002077592],"genre_scores_gemma":[0.1265113,0.0005159159,0.8708602,0.0001231767,0.00008846357,0.0008475725,0.0002436418,0.00008258516,0.000727141],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02282222,"threshold_uncertainty_score":0.1206968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2836707091881809,"score_gpt":0.3801837382328027,"score_spread":0.09651302904462183,"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."}}