{"id":"W2663305152","doi":"10.1002/jae.2580","title":"Weak‐instrument robust inference for two‐sample instrumental variables regression","year":2017,"lang":"en","type":"article","venue":"Journal of Applied Econometrics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Connaught Fund; Hellman Foundation","keywords":"Instrumental variable; Inference; Estimator; Econometrics; Covariate; Mathematics; Statistics; Sample (material); Sample size determination; Monte Carlo method; Regression; Regression analysis; Heteroscedasticity; Variables; Computer science; 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":[0.00144664,0.0001935844,0.0005578989,0.0003464558,0.0003669109,0.0002871133,0.0006333286,0.00009802677,0.0002785335],"category_scores_gemma":[0.006988263,0.0001501575,0.0001312813,0.000146386,0.0001008632,0.0002386902,0.0001655393,0.0002507912,0.00000593697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001544218,"about_ca_system_score_gemma":0.0001135275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000011788,"about_ca_topic_score_gemma":0.000003331286,"domain_scores_codex":[0.9983943,0.00001924763,0.0008430217,0.0002056083,0.0002416023,0.0002961989],"domain_scores_gemma":[0.9944005,0.003123085,0.001667988,0.0004305317,0.0001772802,0.0002006268],"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":[0.0001639654,0.0002010009,0.002566778,0.0001105251,0.00008834223,0.000001907122,0.00008102283,0.00008211051,0.0001830744,0.794267,0.001087235,0.201167],"study_design_scores_gemma":[0.002487938,0.0003856194,0.002251522,0.0001222767,0.00009947181,0.0000141558,0.0002513947,0.003795371,0.002974186,0.9832035,0.004123916,0.0002906445],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1250692,0.00003163736,0.8535638,0.0002006603,0.000937471,0.0003714657,0.0001397308,0.00001484965,0.01967108],"genre_scores_gemma":[0.4474097,0.00004786508,0.5522642,0.00003103304,0.000189478,0.00001077354,0.000001898664,0.00001545513,0.00002960551],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3223405,"threshold_uncertainty_score":0.8366109,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1821843555680151,"score_gpt":0.3780847972627557,"score_spread":0.1959004416947406,"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."}}