{"id":"W2156627773","doi":"10.1002/cjs.11153","title":"Blending domain estimates from two victimization surveys with possible bias","year":2012,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Survey Sampling and Estimation Techniques","field":"Mathematics","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Statistics; Domain (mathematical analysis); Context (archaeology); Small area estimation; Survey data collection; Measure (data warehouse); Econometrics; Survey methodology; Estimation; Survey research; Geography; Computer science; Mathematics; Psychology; Data mining; Engineering; Applied psychology; Archaeology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001872018,0.0001448478,0.0002592368,0.0002764158,0.0001758398,0.0001099231,0.0001429035,0.0000553155,0.0002651993],"category_scores_gemma":[0.001562474,0.0001227874,0.00002992024,0.0001997855,0.00007126369,0.0002761457,0.000006013734,0.0001822482,0.000009194315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001700595,"about_ca_system_score_gemma":0.0004873275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005393391,"about_ca_topic_score_gemma":0.01096226,"domain_scores_codex":[0.998752,0.0001920127,0.0004303539,0.00007830775,0.0002137001,0.0003336167],"domain_scores_gemma":[0.9972028,0.001332274,0.0004295467,0.0001485203,0.0003636883,0.0005231632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003448991,0.00006864562,0.9038656,0.00009611601,0.0002749786,0.0001452711,0.005011321,0.001382937,0.00007640228,0.05185331,0.01843617,0.01875476],"study_design_scores_gemma":[0.002489401,0.0005391321,0.2238201,0.001280103,0.000535707,0.0006535589,0.001772701,0.007326278,0.003972169,0.7529779,0.003343332,0.001289569],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09902028,0.0001414944,0.8996611,0.00005596629,0.0002706615,0.00006885792,0.0004189744,0.00002844963,0.0003342643],"genre_scores_gemma":[0.4342629,0.000006802623,0.5654947,0.00002034861,0.0001234794,9.51077e-7,0.0000425093,0.00002514546,0.00002310566],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7011246,"threshold_uncertainty_score":0.8153229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1084992718008087,"score_gpt":0.3213092735301998,"score_spread":0.2128100017293911,"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."}}