{"id":"W2042833209","doi":"10.2307/3316025","title":"Partially replicated two‐level fractional factorial designs","year":2004,"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":"","funders":"","keywords":"Fractional factorial design; Covariance; Factorial experiment; Constant (computer programming); Series (stratigraphy); Term (time); Mathematics; Factorial; Plackett–Burman design; Construct (python library); Simple (philosophy); Algorithm; Computer science; Statistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002372409,0.00015628,0.0003334178,0.0004224544,0.0002273422,0.0003367365,0.0006658282,0.00008374685,0.001531428],"category_scores_gemma":[0.007688114,0.0001315007,0.00009864748,0.0004680068,0.0002102048,0.0003548827,0.00001641317,0.0003370431,0.00020033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004951736,"about_ca_system_score_gemma":0.004532009,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003443147,"about_ca_topic_score_gemma":0.007220653,"domain_scores_codex":[0.9969893,0.0002539139,0.001035306,0.0002388386,0.001113025,0.0003695951],"domain_scores_gemma":[0.9956713,0.001104852,0.0006237673,0.0003039011,0.001143524,0.001152671],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0008718016,0.0003229096,0.01627388,0.00001158257,0.000432576,0.006012576,0.005085013,0.07685299,0.05975097,0.5223238,0.207497,0.1045648],"study_design_scores_gemma":[0.004355292,0.001280925,0.0324252,0.00006112966,0.00009124942,0.001176188,0.0007935663,0.0009561384,0.01873796,0.8629161,0.07646262,0.0007436008],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006041077,0.00008347072,0.9889222,0.0004182645,0.002569291,0.00009538884,0.0005802147,0.000005433009,0.001284691],"genre_scores_gemma":[0.5266748,0.000002908794,0.4723762,0.0002514001,0.0004591598,0.000001172697,0.000005095114,0.00001581664,0.0002134497],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5206338,"threshold_uncertainty_score":0.9993813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3625785804372562,"score_gpt":0.4497674136179252,"score_spread":0.08718883318066895,"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."}}