{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01041302,0.001040311,0.001824983,0.0009289782,0.0008296118,0.0009816226,0.001990951,0.001413587,0.00917872],"category_scores_gemma":[0.03112584,0.0007844567,0.001289428,0.0009090711,0.001806645,0.001166666,0.001104255,0.001272769,0.001112102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001145863,"about_ca_system_score_gemma":0.001723102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008754448,"about_ca_topic_score_gemma":0.001000026,"domain_scores_codex":[0.9826254,0.01256563,0.000450985,0.001928476,0.001896049,0.0005335172],"domain_scores_gemma":[0.978489,0.01336249,0.001228413,0.004229435,0.002319551,0.0003710604],"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":[0.008273832,0.001484789,0.003722935,0.001093331,0.0004832865,0.0002805961,0.0006292481,0.1955166,0.04628845,0.1657217,0.003414463,0.5730909],"study_design_scores_gemma":[0.002257806,0.007693578,0.005341863,0.0001808279,0.0002715511,0.000198207,0.000157343,0.7196928,0.04218599,0.2030775,0.01872593,0.0002165913],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03289779,0.0001121176,0.963565,0.00008737844,0.00007919555,0.0006761243,0.0001239744,0.0005802223,0.001878243],"genre_scores_gemma":[0.1985631,0.00005393384,0.797258,0.0001197308,0.00004735043,0.00207518,0.0001592381,0.00006601562,0.001657372],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01041302,"threshold_uncertainty_score":0.05506998,"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."}}