{"id":"W2140709916","doi":"10.1002/jcd.21506","title":"Well‐Balanced Designs for Data Placement","year":2015,"lang":"en","type":"article","venue":"Journal of Combinatorial Designs","topic":"DNA and Biological Computing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Abbotsford Veterinary Clinic; University of the Fraser Valley","funders":"Agence Nationale de la Recherche","keywords":"Conjecture; Mathematics; Variance (accounting); Set (abstract data type); Combinatorics; Replication (statistics); Value (mathematics); Server; Expected value; Element (criminal law); File size; Discrete mathematics; Existential quantification; Computer science; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001369519,0.0001305471,0.0002348148,0.00003294295,0.00005709347,0.00004004615,0.0006440022,0.0001358263,0.000005797968],"category_scores_gemma":[0.0006321596,0.00009770063,0.00009493053,0.00006450184,0.00003806939,0.000009738018,0.000184593,0.0001061049,0.00000398118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000266656,"about_ca_system_score_gemma":0.0002333775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000145658,"about_ca_topic_score_gemma":3.967064e-7,"domain_scores_codex":[0.9988523,0.0001184314,0.000392285,0.0001998919,0.0002114901,0.0002256455],"domain_scores_gemma":[0.9987786,0.00006023993,0.0003116608,0.0003112796,0.0003580142,0.000180185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004706744,0.0006821941,0.002244138,0.00003416316,0.0003493475,0.00002855507,0.00006178678,0.0004519472,0.6551972,0.00366547,0.3287784,0.003799979],"study_design_scores_gemma":[0.01347559,0.01487116,0.0002524331,0.00007230829,0.0001692201,0.0001173321,0.0001996889,0.00158865,0.2056321,0.01664962,0.7463241,0.0006477461],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6390907,0.001540615,0.341321,0.0006576662,0.01410524,0.0007853873,0.00003877548,0.00002448832,0.002436225],"genre_scores_gemma":[0.9892816,0.00003202254,0.008204898,0.0001800377,0.002064355,0.000002888724,0.00006250599,0.00001382427,0.0001578915],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4495651,"threshold_uncertainty_score":0.3984116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1355648542630284,"score_gpt":0.3384980479188155,"score_spread":0.2029331936557871,"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."}}