{"id":"W2157130628","doi":"10.1002/cjs.10086","title":"Optimal estimation in surrogate outcome regression problems","year":2010,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Science Fund for Distinguished Young Scholars","keywords":"Outcome (game theory); Estimator; Statistics; Regression analysis; Regression; Propensity score matching; Mathematics; Covariance matrix; Econometrics; Computer science","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":[0.0009511271,0.0001232761,0.000295935,0.0002447298,0.00006741082,0.00006084502,0.0001880608,0.00009431192,0.0004215622],"category_scores_gemma":[0.008165406,0.00009947867,0.00003188975,0.000147948,0.0001148459,0.00008971,0.000008785378,0.0006027215,0.00000998872],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007328564,"about_ca_system_score_gemma":0.0005623166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000732899,"about_ca_topic_score_gemma":0.01716833,"domain_scores_codex":[0.9986307,0.00007834486,0.0007174265,0.00009497332,0.0001962004,0.0002823672],"domain_scores_gemma":[0.9978177,0.0009243505,0.0003516495,0.0001441305,0.0002879755,0.0004741697],"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":[0.00003312904,0.00006556692,0.04353062,0.0002323445,0.00002609418,0.0007909553,0.001339434,0.0005629344,0.0005060103,0.8751464,0.007305282,0.07046121],"study_design_scores_gemma":[0.001008768,0.0002771123,0.05266614,0.0003551274,0.00006118769,0.0002834956,0.0001534409,0.03350424,0.0001896029,0.9091102,0.002036304,0.0003543491],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.218538,0.00002398641,0.779405,0.0002451652,0.0008637948,0.000128287,0.0002378197,0.000005744632,0.0005521749],"genre_scores_gemma":[0.3881896,0.000002464979,0.6116756,0.00002574137,0.00003500469,0.000001170413,0.000002529677,0.00001187944,0.00005596862],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1696516,"threshold_uncertainty_score":0.9775344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1028935983325023,"score_gpt":0.3649809593459968,"score_spread":0.2620873610134945,"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."}}