{"id":"W2084976008","doi":"10.1002/cjs.11174","title":"D‐optimal minimax fractional factorial designs","year":2013,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Minimax; Fractional factorial design; Mathematics; Factorial experiment; Plackett–Burman design; Factorial; Invariant (physics); Optimal design; Mathematical optimization; Applied mathematics; Statistics; Response surface methodology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0015428,0.0001569566,0.0003348673,0.0005059605,0.0001923862,0.0005756181,0.0006799877,0.00009833788,0.01400341],"category_scores_gemma":[0.006178481,0.0001264894,0.0001042744,0.0003411091,0.0002241708,0.0006311196,0.00001781461,0.0003237328,0.0008245278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002569183,"about_ca_system_score_gemma":0.002037391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002578441,"about_ca_topic_score_gemma":0.0007465319,"domain_scores_codex":[0.9970645,0.0003107688,0.0009477604,0.0001914338,0.001099265,0.0003862351],"domain_scores_gemma":[0.9944585,0.002123736,0.0005446001,0.0002226667,0.001388385,0.001262126],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006559506,0.00004614508,0.007552873,0.000003324989,0.00008314432,0.0004369981,0.001341905,0.001831465,0.00650824,0.01352088,0.9241287,0.0444807],"study_design_scores_gemma":[0.003519478,0.003145192,0.1255513,0.00008186988,0.0001464426,0.001708813,0.007218498,0.01462366,0.007907743,0.3093999,0.5250378,0.001659295],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02904815,0.0001587356,0.9627767,0.000341053,0.00406196,0.0001489729,0.0003131012,0.000004522936,0.003146848],"genre_scores_gemma":[0.4014748,0.000003209891,0.5967094,0.0002097242,0.0005936492,0.000002367662,0.000003189338,0.00001714656,0.0009865995],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3990909,"threshold_uncertainty_score":0.9999534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1962650104295456,"score_gpt":0.4038326614090677,"score_spread":0.2075676509795221,"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."}}