{"id":"W3119329857","doi":"10.1002/cjs.11586","title":"An approximate Bayesian inference on propensity score estimation under unit nonresponse","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Frequentist inference; Statistics; Propensity score matching; Bayesian probability; Econometrics; Mathematics; Weighting; Statistical inference; Bayesian inference; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0226898,0.0008689649,0.002213717,0.002417368,0.001120864,0.001607948,0.002825633,0.001767937,0.004589775],"category_scores_gemma":[0.1109398,0.001036851,0.001739929,0.003679662,0.001946974,0.003746397,0.002638099,0.002817169,0.0007253914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001689974,"about_ca_system_score_gemma":0.003351077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01033768,"about_ca_topic_score_gemma":0.006640578,"domain_scores_codex":[0.9836046,0.01228482,0.0005054813,0.001433137,0.001831326,0.0003405988],"domain_scores_gemma":[0.958654,0.03356209,0.00216462,0.002739,0.002575221,0.000305132],"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":[0.0001876341,0.0001545753,0.005984199,0.0005352322,0.000393181,0.0002598875,0.0007366966,0.2232456,0.0008399325,0.5278988,0.003943075,0.2358211],"study_design_scores_gemma":[0.00009420681,0.00006912941,0.00181845,0.0001114643,0.0001167896,0.0001407887,0.00009660352,0.6251414,0.0004534377,0.3681199,0.003788711,0.00004911819],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003799338,0.0001782535,0.9950134,0.0002198694,0.00002161171,0.0000563955,0.0000532448,0.00007199714,0.0005858574],"genre_scores_gemma":[0.3097215,0.001728284,0.681792,0.0005543053,0.0003504181,0.001143417,0.0006969069,0.0001327529,0.003880375],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0226898,"threshold_uncertainty_score":0.1199966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2382447312296052,"score_gpt":0.3957939407962062,"score_spread":0.1575492095666011,"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."}}