{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006834463,0.001486731,0.001221282,0.001669961,0.0008021818,0.002178571,0.001138622,0.001774773,0.005815825],"category_scores_gemma":[0.01832176,0.001171367,0.0007263452,0.001528008,0.00140068,0.003850698,0.001458014,0.001301703,0.001392585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001633038,"about_ca_system_score_gemma":0.001125717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000379245,"about_ca_topic_score_gemma":0.0004785998,"domain_scores_codex":[0.9943569,0.00290323,0.0003386817,0.0008007697,0.001145005,0.0004552925],"domain_scores_gemma":[0.9776619,0.01230736,0.003651903,0.002638752,0.002824431,0.0009157113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007694963,0.0003210425,0.003269273,0.0004842999,0.0001193944,0.0002333325,0.0003005679,0.3611499,0.02011938,0.5120584,0.00548785,0.09568708],"study_design_scores_gemma":[0.0002457832,0.0008979952,0.0007938892,0.0001565759,0.00005156967,0.0004205204,0.0001278995,0.5183792,0.008236006,0.461101,0.009521892,0.0000677329],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0478781,0.0006399607,0.9455974,0.0005301677,0.00008697104,0.0001738626,0.000249011,0.0003107326,0.004533885],"genre_scores_gemma":[0.5353,0.0008532002,0.4571015,0.0004532085,0.0002084958,0.0007056592,0.0005286584,0.0002015696,0.004647721],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006834463,"threshold_uncertainty_score":0.0361445,"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."}}