{"id":"W2101423867","doi":"10.1016/j.spl.2014.07.032","title":"Space-filling Latin hypercube designs based on randomization restrictions in factorial experiments","year":2014,"lang":"en","type":"article","venue":"Statistics & Probability Letters","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"Acadia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Latin hypercube sampling; Fractional factorial design; Randomization; Factorial; Factorial experiment; Space (punctuation); Statistics; Combinatorics; Econometrics; Monte Carlo method; Computer science; Mathematical analysis; Randomized controlled trial","routes":{"ca_aff":true,"ca_fund":true,"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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.005027935,0.0002882843,0.0004927124,0.0004011127,0.0002118528,0.0002735677,0.0004559109,0.0001140793,0.0001980038],"category_scores_gemma":[0.01502361,0.0002513372,0.00009966964,0.0008277565,0.0002050285,0.0002268761,0.00006075773,0.0002880795,0.000101244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003830465,"about_ca_system_score_gemma":0.00008939449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001932123,"about_ca_topic_score_gemma":0.00003561577,"domain_scores_codex":[0.9935264,0.002717325,0.001021133,0.0008623316,0.00144402,0.0004288016],"domain_scores_gemma":[0.9909086,0.007688294,0.0002775199,0.0007891962,0.0001738085,0.0001626321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.007222747,0.002278862,0.08683908,0.00006814973,0.00006092644,0.00003963893,0.006377697,0.2164131,0.4577365,0.1801515,0.01948351,0.02332824],"study_design_scores_gemma":[0.01416067,0.0009209149,0.02605143,0.00009124271,0.00004441681,0.000001795444,0.0001274935,0.4716612,0.03223498,0.4512912,0.002187924,0.001226702],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1025026,0.000005827378,0.8942771,0.000548644,0.001059282,0.0008487807,0.00006567523,0.00005699931,0.0006350878],"genre_scores_gemma":[0.3881253,8.415645e-7,0.6111013,0.0005106457,0.0001410506,0.00005194366,0.00002096018,0.00002124902,0.00002674427],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4255015,"threshold_uncertainty_score":0.9999939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1681913532010991,"score_gpt":0.4025455546473535,"score_spread":0.2343542014462544,"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."}}