{"id":"W4220729324","doi":"10.1093/ectj/utac008","title":"Estimation and inference on treatment effects under treatment-based sampling designs","year":2022,"lang":"en","type":"article","venue":"Econometrics Journal","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Japan Society for the Promotion of Science; Social Sciences and Humanities Research Council of Canada","keywords":"Estimator; Population; Inference; Sampling (signal processing); Benchmark (surveying); Sampling design; Computer science; Sample size determination; Statistics; Econometrics; Causal inference; Statistical inference; Sample (material); Mathematics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000369505,0.0002117556,0.000293368,0.0008699112,0.0004503396,0.0001180072,0.000108146,0.00004135189,0.0001837379],"category_scores_gemma":[0.0005367568,0.0001773111,0.00007819788,0.0004528181,0.00002854603,0.0001692468,0.00003267888,0.0002066262,0.000006646953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001895875,"about_ca_system_score_gemma":0.0001231221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005896853,"about_ca_topic_score_gemma":0.000002625589,"domain_scores_codex":[0.9989623,0.0001182456,0.0003072065,0.0002112139,0.000161309,0.0002397221],"domain_scores_gemma":[0.9963061,0.003041883,0.0002901431,0.000196532,0.00003322339,0.0001321684],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001891201,0.002217902,0.006911979,0.00007944213,0.000421057,0.0001024822,0.0009017987,0.1046721,0.000597137,0.1264485,0.000205407,0.7572531],"study_design_scores_gemma":[0.003498095,0.01265253,0.002652792,0.00007432819,0.0002051507,0.0001908484,0.0002660397,0.04647751,0.01317865,0.9190397,0.001064484,0.0006999297],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3783176,0.0001754167,0.6204314,0.0001405538,0.000124815,0.0003174077,0.00001450769,0.0001015205,0.0003768642],"genre_scores_gemma":[0.9053736,0.000108448,0.09416527,0.00009737643,0.00003883277,0.0001091021,0.000007225337,0.00002601224,0.00007410416],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7925912,"threshold_uncertainty_score":0.7230536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5126904252324965,"score_gpt":0.4566435585241612,"score_spread":0.05604686670833536,"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."}}