{"id":"W3209199114","doi":"10.1371/journal.pcbi.1009471","title":"Building and experimenting with an agent-based model to study the population-level impact of CommunityRx, a clinic-based community resource referral intervention","year":2021,"lang":"en","type":"article","venue":"PLoS Computational Biology","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Argonne National Laboratory; National Institute on Minority Health and Health Disparities; National Institute on Aging; Office of Science; National Institutes of Health; U.S. Department of Health and Human Services; National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; U.S. Department of Energy","keywords":"Agent-based model; Population; Intervention (counseling); Computer science; Fidelity; Psychological intervention; Referral; Clinical trial; Resource (disambiguation); Medicine; Artificial intelligence; Nursing; Environmental health","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00281176,0.0008677879,0.0009914119,0.0007575842,0.0006645196,0.001508069,0.00147083,0.002352081,0.004630973],"category_scores_gemma":[0.01277954,0.000542101,0.001018885,0.0007062628,0.0009671592,0.001242954,0.001064923,0.001808291,0.0003341355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002099639,"about_ca_system_score_gemma":0.002834221,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03028148,"about_ca_topic_score_gemma":0.01601583,"domain_scores_codex":[0.9990632,0.0005450271,0.0000380791,0.0001547568,0.00007651284,0.0001224904],"domain_scores_gemma":[0.9896069,0.008755519,0.0005571358,0.0002157891,0.0005011667,0.0003634453],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001166371,0.0001607415,0.004030541,0.00007382636,0.00005397488,0.00009551371,0.0001152878,0.9839016,0.0003017778,0.008409305,0.0004211561,0.002319667],"study_design_scores_gemma":[0.0001239039,0.000108341,0.0004782818,0.00001346938,0.00003555873,0.00001050469,0.00006675616,0.9952372,0.000122208,0.003290091,0.0005000959,0.00001361607],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7887772,0.0005566646,0.1843843,0.004208661,0.0002130173,0.00101768,0.002811416,0.0003534349,0.01767769],"genre_scores_gemma":[0.9498678,0.000266612,0.0439189,0.0003821,0.00002724564,0.001166361,0.0005930602,0.00002375774,0.003754157],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03028148,"threshold_uncertainty_score":0.06021047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.435473661953945,"score_gpt":0.4918733350779487,"score_spread":0.05639967312400368,"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."}}