{"id":"W2322253843","doi":"10.1097/ede.0000000000000053","title":"Constructing Inverse Probability Weights for Continuous Exposures","year":2014,"lang":"en","type":"article","venue":"Epidemiology","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":139,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; McGill University","funders":"","keywords":"Heteroscedasticity; Homoscedasticity; Mathematics; Statistics; Probability distribution; Quantile","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.003486744,0.0001768368,0.0007159191,0.00004850733,0.00008492949,0.000003843242,0.0001909003,0.000212566,0.00005188261],"category_scores_gemma":[0.05429586,0.0001447855,0.0001175142,0.00005070409,0.0003407832,0.00008000354,0.00006568544,0.000186863,0.00001070353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007040641,"about_ca_system_score_gemma":0.00002354161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001908797,"about_ca_topic_score_gemma":0.0000945081,"domain_scores_codex":[0.997816,0.0006734707,0.0006667675,0.000367955,0.00004677967,0.000429058],"domain_scores_gemma":[0.9810137,0.01793308,0.0003831954,0.0004483358,0.0001375334,0.00008419387],"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":[0.00001790415,0.00002165878,0.02892642,0.00006791781,0.00001381756,3.095183e-7,0.00006154238,0.000001451966,0.0002017333,0.9563742,0.005699419,0.008613566],"study_design_scores_gemma":[0.0002342066,0.0001921026,0.0002601005,0.00002560023,0.0000161339,0.00001390648,0.00005961957,0.0007779596,0.002765299,0.9889675,0.006530158,0.0001574497],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2165886,0.00002384685,0.7753249,0.00105516,0.000235416,0.0007514266,0.00001097861,0.0005600468,0.005449575],"genre_scores_gemma":[0.2197077,0.000003352881,0.7790392,0.0006504866,0.0001992761,0.0002091274,0.000009194968,0.00002163245,0.000160071],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05080912,"threshold_uncertainty_score":0.9536702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.266417665166968,"score_gpt":0.4377748148809384,"score_spread":0.1713571497139704,"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."}}