{"id":"W2083828390","doi":"10.1016/j.jspi.2005.02.018","title":"Constructing non-regular robust parameter designs","year":2005,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University; University of British Columbia","funders":"","keywords":"Fractional factorial design; Mathematics; Selection (genetic algorithm); Orthogonal array; Variance (accounting); Mathematical optimization; Design of experiments; Rank (graph theory); Optimal design; Noise (video); Word (group theory); Factorial experiment; Algorithm; Statistics; Computer science; Artificial intelligence; Combinatorics","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":[0.05945624,0.001534356,0.003515562,0.002163882,0.0006456988,0.001695961,0.00393318,0.002652503,0.003165708],"category_scores_gemma":[0.1764207,0.002698672,0.00277096,0.001202334,0.003870948,0.002928846,0.003489098,0.00320604,0.0006949652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001053518,"about_ca_system_score_gemma":0.002642971,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004736734,"about_ca_topic_score_gemma":0.000617884,"domain_scores_codex":[0.9505114,0.04108988,0.001528647,0.00407514,0.002359657,0.0004352679],"domain_scores_gemma":[0.7750347,0.1887535,0.007645896,0.024079,0.003692363,0.0007945452],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002835003,0.0004031886,0.003689071,0.001433067,0.001437272,0.0002482236,0.0005559707,0.3939677,0.005751561,0.2871581,0.002344383,0.3001764],"study_design_scores_gemma":[0.0004757943,0.0006811855,0.0008650685,0.0001072192,0.0002523543,0.00007858085,0.00004286872,0.5892579,0.00324072,0.4023969,0.002549843,0.00005151379],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004541194,0.00007747968,0.9947319,0.00006067425,0.00001516735,0.0001195806,0.00004383133,0.0001636821,0.0002464573],"genre_scores_gemma":[0.1010372,0.0001048851,0.8969982,0.0001152014,0.00003923032,0.0010077,0.0001861014,0.0001278043,0.0003837416],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05945624,"threshold_uncertainty_score":0.3144384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2522636315418321,"score_gpt":0.4727185011069364,"score_spread":0.2204548695651043,"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."}}