{"id":"W4401037694","doi":"10.1002/sim.10167","title":"Modern approaches for evaluating treatment effect heterogeneity from clinical trials and observational data","year":2024,"lang":"en","type":"review","venue":"Statistics in Medicine","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bayer (Canada)","funders":"","keywords":"Observational study; Computer science; Identification (biology); Rule of thumb; Clinical trial; Medical physics; Machine learning; Artificial intelligence; Medicine; Statistics; Mathematics; Algorithm","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","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.01609894,0.0005778272,0.004963802,0.0001354301,0.000044535,0.00003006069,0.0004069687,0.0003587962,0.00002055593],"category_scores_gemma":[0.05985688,0.0003349606,0.0001518576,0.000120711,0.0002233102,0.00005787926,0.0002694324,0.0004755424,0.000002637093],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002182936,"about_ca_system_score_gemma":0.0002807428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003104876,"about_ca_topic_score_gemma":0.00009487042,"domain_scores_codex":[0.9934943,0.002044147,0.002802622,0.0009983415,0.0004102376,0.0002503917],"domain_scores_gemma":[0.930124,0.06781968,0.0009033628,0.0009915729,0.0000636356,0.00009768207],"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":[0.00002449691,0.00005273673,0.00001326172,0.01041631,0.0004621109,0.00001103976,0.00006042682,3.315997e-7,2.572299e-7,0.01539532,0.00241627,0.9711474],"study_design_scores_gemma":[0.001197094,0.001383629,0.000004125835,0.01888468,0.01045766,0.00000657527,0.00001313961,0.03198895,8.738142e-7,0.8836094,0.05207408,0.0003798499],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000008143533,0.6042439,0.3843291,0.00002487543,0.0002312445,0.002573259,0.008512603,0.00006205607,0.0000148037],"genre_scores_gemma":[0.000002455974,0.602544,0.3892054,0.00001128513,0.0004810776,0.0006537865,0.0070103,0.00006079588,0.00003097157],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9707676,"threshold_uncertainty_score":0.9999102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9530672804330427,"score_gpt":0.7219823764569416,"score_spread":0.231084903976101,"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."}}