{"id":"W1973360772","doi":"10.1016/j.jspi.2009.02.010","title":"De-aliasing effects using semifoldover techniques","year":2009,"lang":"en","type":"article","venue":"Journal of Statistical Planning and Inference","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Factor (programming language); Aliasing; Factorial experiment; Fractional factorial design; Factorial; Plackett–Burman design; Design of experiments; Statistics; Arithmetic; Computer science; Programming language; Artificial intelligence; Response surface methodology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002429567,0.000111078,0.0003246697,0.0001783847,0.00009545842,0.0003316773,0.0002090674,0.00006613702,0.00003609438],"category_scores_gemma":[0.007480277,0.00007718079,0.0000387744,0.0001817443,0.0001000365,0.0003977224,0.000034763,0.0002553272,0.0000021319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000457459,"about_ca_system_score_gemma":0.00007614173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005339027,"about_ca_topic_score_gemma":2.432618e-8,"domain_scores_codex":[0.998195,0.0002941781,0.0005484234,0.0001488803,0.000613885,0.000199623],"domain_scores_gemma":[0.9953499,0.003868616,0.0003108087,0.00009703294,0.0001839426,0.0001896968],"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":[0.0003233468,0.0001391876,0.02834294,0.00002221959,0.00002871712,0.0007121676,0.001696035,0.0005837266,0.3345441,0.02538382,0.00311014,0.6051136],"study_design_scores_gemma":[0.0009301426,0.00428151,0.2158614,0.001465337,0.0001066363,0.001737443,0.00100559,0.06356848,0.1216142,0.5869138,0.001815301,0.0007000875],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1685237,0.0004279309,0.8294976,0.00005659564,0.00008332863,0.00003557093,0.000003253766,0.0000104291,0.001361515],"genre_scores_gemma":[0.5712636,0.000005673769,0.4284505,0.0002187792,0.00004493271,1.140234e-7,9.599745e-8,0.000002575562,0.00001378797],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6044135,"threshold_uncertainty_score":0.8955131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1496450414730653,"score_gpt":0.5156544275279231,"score_spread":0.3660093860548579,"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."}}