{"id":"W2028152993","doi":"10.1002/cjs.5550340112","title":"Imputation using response probability","year":2006,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Imputation (statistics); Mathematics; Estimator; Statistics; Missing data","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001122135,0.0001037174,0.0002303532,0.0001623177,0.000114013,0.00006851856,0.0001204033,0.00005922161,0.0001850985],"category_scores_gemma":[0.005253365,0.0000940555,0.00003990028,0.0001540225,0.0001417459,0.00007592951,0.000004970627,0.0001736351,0.000003195644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002603279,"about_ca_system_score_gemma":0.001527238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002035741,"about_ca_topic_score_gemma":0.004110418,"domain_scores_codex":[0.998629,0.000275422,0.0005712326,0.00009003985,0.0001839863,0.000250312],"domain_scores_gemma":[0.9970951,0.001640582,0.0003239481,0.0001189085,0.0005129438,0.0003085163],"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":[0.00008615584,0.00002644082,0.002764899,0.00006210363,0.00001587519,0.0003552781,0.0001648099,0.00005888836,0.0003426116,0.978438,0.006307695,0.01137727],"study_design_scores_gemma":[0.0002051011,0.0001077278,0.01203279,0.00004805048,0.00004845342,0.000151837,0.00003408276,0.001603189,0.0001047089,0.9850044,0.0005519577,0.0001076519],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.07276505,0.00002889699,0.9262751,0.000108551,0.0002202307,0.00007982142,0.0003302322,0.000004321107,0.0001877437],"genre_scores_gemma":[0.2103361,4.713239e-7,0.7895006,0.00002485423,0.00009650933,4.447785e-7,0.000001777723,0.00001220499,0.00002698878],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1375711,"threshold_uncertainty_score":0.6289148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07531166977525713,"score_gpt":0.3441406675702469,"score_spread":0.2688289977949897,"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."}}