{"id":"W4412173418","doi":"10.1017/rsm.2025.10021","title":"Regression augmented weighting adjustment for indirect comparisons in health decision modelling","year":2025,"lang":"en","type":"article","venue":"Research Synthesis Methods","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Weighting; Computer science; Regression analysis; Econometrics; Statistics; Regression; Machine learning; Mathematics; Medicine","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02569179,0.000230198,0.0007898993,0.001185554,0.0003763894,0.00004917974,0.0004674167,0.0001791235,0.00003415877],"category_scores_gemma":[0.02527869,0.00018799,0.0001197632,0.001124221,0.00009704023,0.0001416294,0.00029957,0.0006454212,0.000002241135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000982528,"about_ca_system_score_gemma":0.0003228486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001035315,"about_ca_topic_score_gemma":0.00004372301,"domain_scores_codex":[0.9929653,0.003978086,0.000940424,0.000590542,0.0006160132,0.0009096197],"domain_scores_gemma":[0.9330177,0.06566726,0.0002175215,0.0006647255,0.0002905097,0.0001422683],"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":[0.0002827421,0.000394168,0.0001452553,0.0008237957,0.00004929612,0.00000232522,0.0003285497,0.0006831601,0.004548033,0.08255699,0.006626704,0.903559],"study_design_scores_gemma":[0.0002747535,0.00009578522,0.00005933554,0.004677886,0.00001095265,6.993475e-7,0.0004950652,0.2032897,0.1582238,0.6268229,0.005876626,0.0001723937],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003060746,0.00119363,0.9917498,0.0007803959,0.00008686779,0.001618354,0.000008743772,0.0002139097,0.001287553],"genre_scores_gemma":[0.01869961,0.0006443611,0.9791272,0.0000341971,0.00003304892,0.001074822,0.000002860896,0.00003992589,0.0003439689],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9033866,"threshold_uncertainty_score":0.9829318,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6488356191652721,"score_gpt":0.6639908171596867,"score_spread":0.01515519799441456,"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."}}