{"id":"W2184934817","doi":"10.1002/cjs.11461","title":"Benchmarked small area prediction","year":2018,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Agricultural Statistics Service; Natural Resources Conservation Service; U.S. Department of Agriculture; National Science Foundation","keywords":"Benchmarking; Estimator; Variance (accounting); Constraint (computer-aided design); Statistics; Computer science; Function (biology); Small area estimation; Econometrics; Mathematics; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007490345,0.0007469612,0.001259695,0.0009896363,0.0004682913,0.001930876,0.002311635,0.0009210299,0.005712596],"category_scores_gemma":[0.02977121,0.000391428,0.000617236,0.001848768,0.0006391262,0.00197528,0.001323948,0.001608151,0.001006971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001483576,"about_ca_system_score_gemma":0.001859997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01947319,"about_ca_topic_score_gemma":0.0141993,"domain_scores_codex":[0.9965053,0.001612492,0.0001536805,0.0008312973,0.0006368658,0.0002603545],"domain_scores_gemma":[0.9838805,0.008614257,0.001231155,0.002559409,0.003362525,0.0003521492],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002070429,0.0001057228,0.01888302,0.00006520053,0.0001157555,0.00006684774,0.00006874028,0.8703422,0.001123385,0.0110379,0.00506475,0.09291942],"study_design_scores_gemma":[0.000009531687,0.00003964256,0.002509051,0.00001368835,0.00000852503,0.00001035862,0.00002005937,0.9878837,0.0009237143,0.007659227,0.0009069636,0.00001549953],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09809003,0.0002455357,0.8934088,0.0002623663,0.0001305729,0.0001203688,0.001563112,0.001970844,0.004208412],"genre_scores_gemma":[0.8285322,0.00009367293,0.1655553,0.00009912665,0.00004988343,0.0001660593,0.002969785,0.0002520462,0.002281973],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01947319,"threshold_uncertainty_score":0.03961325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0147854357451368,"score_gpt":0.2036071508238392,"score_spread":0.1888217150787024,"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."}}