{"id":"W303565404","doi":"10.1002/cjs.5550330201","title":"Inference for domains under imputation for missing survey data","year":2005,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Survey Methodology and Nonresponse","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; Statistics Canada","funders":"","keywords":"Imputation (statistics); Estimator; Missing data; Inference; Statistics; Econometrics; Efficiency; Best linear unbiased prediction; Mathematics; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.07020499,0.001183382,0.002942392,0.003933105,0.0006853744,0.003152597,0.003390099,0.001958812,0.00200689],"category_scores_gemma":[0.3451486,0.001172865,0.002418736,0.005626692,0.00300066,0.004847937,0.003509497,0.003074539,0.0005487292],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001441208,"about_ca_system_score_gemma":0.001988461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002051392,"about_ca_topic_score_gemma":0.001084429,"domain_scores_codex":[0.9489796,0.04216704,0.001555786,0.00307107,0.003534158,0.0006923359],"domain_scores_gemma":[0.5459714,0.4135025,0.01198658,0.01849086,0.009063998,0.0009846382],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005116935,0.0002377346,0.04039156,0.0009711921,0.002265609,0.0002518018,0.00116885,0.3368198,0.0005107482,0.4297408,0.004814738,0.1823155],"study_design_scores_gemma":[0.0001028309,0.0001570614,0.004915812,0.0002030805,0.000303115,0.0001707272,0.000251318,0.6081358,0.001270714,0.3805135,0.003911455,0.00006453242],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01739872,0.0005674068,0.9802842,0.0004100683,0.00005776024,0.00007201533,0.0001359461,0.0001410877,0.0009328968],"genre_scores_gemma":[0.4864723,0.002002133,0.5048363,0.0006328825,0.0003450916,0.0007228893,0.001721924,0.0002093217,0.003057175],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07020499,"threshold_uncertainty_score":0.3712839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5591886833785065,"score_gpt":0.4977585733560223,"score_spread":0.06143011002248416,"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."}}