{"id":"W2111666498","doi":"10.1093/biomet/ass065","title":"Strong orthogonal arrays and associated Latin hypercubes for computer experiments","year":2012,"lang":"en","type":"article","venue":"Biometrika","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":96,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Latin hypercube sampling; Hypercube; Beijing; China; Mathematics; Library science; Combinatorics; Statistics; Computer science; Geography; Monte Carlo method; Archaeology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01036559,0.001457871,0.00141692,0.001004781,0.0004884751,0.001866531,0.001243146,0.001067149,0.005360227],"category_scores_gemma":[0.03155645,0.0006345529,0.001172525,0.001673187,0.002276255,0.00217741,0.001827406,0.002209099,0.00159893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006945666,"about_ca_system_score_gemma":0.001161755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00020638,"about_ca_topic_score_gemma":0.0002010022,"domain_scores_codex":[0.9815749,0.01438291,0.0006956747,0.001249552,0.001818375,0.0002786322],"domain_scores_gemma":[0.9716781,0.02227437,0.001782196,0.002433803,0.001530656,0.0003008782],"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":[0.0007263598,0.0001215207,0.0008119714,0.000739025,0.0001605698,0.0001108456,0.0002798736,0.1243243,0.01009365,0.6823647,0.003038417,0.1772288],"study_design_scores_gemma":[0.0002539666,0.001024748,0.0004578668,0.0001642186,0.00006343041,0.0001379811,0.0001042723,0.2735908,0.008016651,0.6883167,0.02777705,0.00009216062],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001549953,0.0002427974,0.9965146,0.00007985712,0.00006614494,0.00009141793,0.00006023329,0.0001177434,0.001277232],"genre_scores_gemma":[0.06004304,0.0007441915,0.9338765,0.0002900836,0.0002155577,0.00305536,0.0002062336,0.0001192976,0.001449734],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01036559,"threshold_uncertainty_score":0.05481917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2075949699799988,"score_gpt":0.3704516957843537,"score_spread":0.162856725804355,"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."}}