{"id":"W1993481816","doi":"10.1002/cjs.11190","title":"The factor aliased effect number pattern and its application in experimental planning","year":2013,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; McMaster University","funders":"National Natural Science Foundation of China","keywords":"Fractional factorial design; Rank (graph theory); Ranking (information retrieval); Factorial experiment; Factor (programming language); Design of experiments; Computer science; Statistics; Paired comparison; Mathematics; Machine learning; Combinatorics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.07238244,0.001399452,0.00296336,0.003688508,0.001296128,0.002020204,0.002801161,0.002775358,0.00877996],"category_scores_gemma":[0.2470281,0.001216094,0.002166868,0.00403357,0.006222091,0.003996516,0.002162514,0.003268398,0.0009384061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002800414,"about_ca_system_score_gemma":0.003139127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002070477,"about_ca_topic_score_gemma":0.001802757,"domain_scores_codex":[0.9354287,0.04687666,0.002328028,0.007070473,0.007659256,0.0006367441],"domain_scores_gemma":[0.7393838,0.2027513,0.01254639,0.03190969,0.01202511,0.001383633],"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":[0.001863616,0.0003313306,0.009361341,0.00122257,0.0004011212,0.000429505,0.0008271126,0.1229356,0.007141541,0.3987657,0.004152331,0.4525682],"study_design_scores_gemma":[0.0003670165,0.00147559,0.005688115,0.0002774873,0.0001688375,0.0002635878,0.0001114473,0.5421275,0.005598772,0.434951,0.008807522,0.0001631657],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004930572,0.0001314956,0.9935805,0.0001505022,0.00003533933,0.0002111604,0.00007295427,0.0001802322,0.0007073],"genre_scores_gemma":[0.1035141,0.0001378811,0.8939827,0.0001404675,0.00003921157,0.0009304605,0.00009655458,0.0001160179,0.00104262],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07238244,"threshold_uncertainty_score":0.3827995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08315733229787388,"score_gpt":0.4071847278924204,"score_spread":0.3240273955945466,"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."}}