{"id":"W4399754935","doi":"10.1080/26941899.2024.2360892","title":"Model Selection for Exposure-Mediator Interaction","year":2024,"lang":"en","type":"article","venue":"Data Science in Science","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; Eisai Incorporated; Canadian Institutes of Health Research; University of Southern California; AbbVie Canada; National Institutes of Health; Genentech; Takeda Pharmaceutical Company; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Alzheimer's Disease Neuroimaging Initiative; GE Healthcare; Pfizer; Biogen; BioClinica; Roche; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Meso Scale Diagnostics; Novartis Pharmaceuticals Corporation; Merck; Alzheimer's Association","keywords":"Mediator; Selection (genetic algorithm); Psychology; Computer science; Medicine; Artificial intelligence; Internal medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03666107,0.002493774,0.003258963,0.002330779,0.001645996,0.001706213,0.004066697,0.002303374,0.009436379],"category_scores_gemma":[0.05092893,0.001029191,0.004771364,0.002528665,0.001370453,0.001707424,0.002731172,0.004592246,0.00127142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001082929,"about_ca_system_score_gemma":0.004684645,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006050504,"about_ca_topic_score_gemma":0.006461659,"domain_scores_codex":[0.9746687,0.02178778,0.0005663877,0.001698955,0.0007958347,0.0004823075],"domain_scores_gemma":[0.9636204,0.03202059,0.0008557576,0.001764372,0.001352052,0.0003868167],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002888983,0.0009090828,0.04842761,0.001553665,0.007128093,0.003116053,0.001911426,0.4132146,0.005024012,0.1696377,0.01708729,0.3291015],"study_design_scores_gemma":[0.0003403265,0.0003070965,0.002226137,0.00007614987,0.0004717154,0.0001838096,0.0001333252,0.9273555,0.0008688055,0.06477947,0.003205891,0.00005191881],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01141292,0.0003188683,0.9861581,0.0005898361,0.00009438404,0.0003680806,0.0002575283,0.0004590263,0.0003412793],"genre_scores_gemma":[0.3258449,0.0005184945,0.6633703,0.0007522357,0.0003905165,0.003830854,0.001565808,0.0002892388,0.003437724],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03666107,"threshold_uncertainty_score":0.1938846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.405217553711427,"score_gpt":0.5323269213190341,"score_spread":0.1271093676076072,"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."}}