{"id":"W1493983723","doi":"10.2139/ssrn.1617262","title":"Efficient Estimation of Average Treatment Effects Under Treatment-Based Sampling, Second Version","year":2010,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Statistics; Estimation; Sampling (signal processing); Mathematics; Econometrics; Computer science; Economics; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.05839758,0.002108372,0.007783552,0.002723919,0.001320776,0.004335331,0.006405432,0.00490619,0.01584355],"category_scores_gemma":[0.215848,0.003706765,0.004813625,0.004364124,0.004532744,0.005323856,0.003115798,0.006524085,0.001530373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00235209,"about_ca_system_score_gemma":0.006023499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006538881,"about_ca_topic_score_gemma":0.005704623,"domain_scores_codex":[0.9493628,0.03937007,0.001656616,0.005402763,0.002809934,0.001397859],"domain_scores_gemma":[0.7498331,0.2148121,0.005393072,0.0246651,0.004230981,0.001065646],"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":[0.003700149,0.0009538899,0.009435633,0.003167773,0.004607533,0.0005910724,0.001253092,0.1881298,0.002185575,0.4166571,0.01384548,0.3554729],"study_design_scores_gemma":[0.0008937567,0.0005370555,0.004419988,0.0003040628,0.00115117,0.0003402899,0.0001487355,0.5369089,0.002039472,0.449241,0.00391979,0.00009589268],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01024581,0.000616087,0.9858146,0.0006831028,0.0001958312,0.0004799097,0.0006245477,0.0003407405,0.0009994912],"genre_scores_gemma":[0.3947112,0.002213441,0.5853549,0.001149083,0.0008866044,0.003250985,0.002258789,0.0003234177,0.009851596],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05839758,"threshold_uncertainty_score":0.3088396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0482642513468771,"score_gpt":0.3639097914497442,"score_spread":0.3156455401028671,"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."}}