{"id":"W2905188466","doi":"10.1007/s00184-018-0702-z","title":"Some properties of foldover designs with column permutations","year":2018,"lang":"en","type":"article","venue":"Metrika","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Column (typography); Mathematics; Column generation; Optimal design; Mathematical optimization; Function (biology); Applied mathematics; Statistics; Geometry","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":[],"consensus_categories":[],"category_scores_codex":[0.001896134,0.0001261268,0.0002957971,0.0004297741,0.0001501553,0.0001340801,0.0005176616,0.00005133502,0.0005547834],"category_scores_gemma":[0.002378241,0.00007781876,0.00007490203,0.001666344,0.0005681756,0.0005312785,0.00008945886,0.00006337914,0.0003365104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003879783,"about_ca_system_score_gemma":0.0001066585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006373932,"about_ca_topic_score_gemma":0.00001454795,"domain_scores_codex":[0.9974621,0.0003477346,0.0004347472,0.0003507593,0.001187878,0.0002167991],"domain_scores_gemma":[0.9981061,0.000575536,0.0001928024,0.0004872958,0.0005478137,0.00009050179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004418535,0.000316896,0.009063251,0.00001171054,0.0000884183,0.000007638058,0.004145018,0.00008024626,0.9553689,0.01009999,0.004885552,0.0154905],"study_design_scores_gemma":[0.0004763959,0.001093597,0.006659205,0.00002606392,0.00002271231,0.000009112856,0.001747508,0.0009285709,0.9803903,0.00528811,0.003169074,0.0001893269],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9356642,0.001323111,0.05457242,0.000174131,0.0003263104,0.0004380278,0.00001240774,0.00005516251,0.007434221],"genre_scores_gemma":[0.8956702,0.000003963974,0.1007045,0.0001239389,0.0001054081,0.00002129449,3.867324e-7,0.000014707,0.003355595],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04613208,"threshold_uncertainty_score":0.6074489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3358189822527115,"score_gpt":0.4444268068932322,"score_spread":0.1086078246405207,"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."}}