{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002893843,0.0001362537,0.0002791233,0.000231984,0.0005531721,0.000101981,0.0003965283,0.00005465769,0.00003301141],"category_scores_gemma":[0.0007255335,0.00008951377,0.0001036535,0.0005292732,0.0001036076,0.0001059108,0.0001437256,0.0002488496,0.000001787588],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003077369,"about_ca_system_score_gemma":0.00008256728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006607252,"about_ca_topic_score_gemma":0.0005012542,"domain_scores_codex":[0.9957337,0.00271899,0.0006781069,0.0002800012,0.0004368651,0.0001523253],"domain_scores_gemma":[0.995994,0.002477002,0.0003503178,0.0004947352,0.0006072659,0.00007666327],"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":[0.0003166754,0.001206408,0.1523855,0.000004985546,0.00009463974,8.195401e-7,0.001844866,0.8384833,0.0006300491,0.0003991578,0.00001047413,0.004623132],"study_design_scores_gemma":[0.0009072971,0.0009611212,0.2125013,0.00002840468,0.00002866401,0.000001583499,0.003718097,0.771858,0.0000722925,0.009829694,0.000001066332,0.00009246845],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7912459,0.00001988534,0.208248,0.0001866196,0.00001599951,0.0001978828,0.00004046159,0.00002135179,0.00002385709],"genre_scores_gemma":[0.9603422,1.820275e-7,0.03910156,0.0002621954,0.000008595497,0.00002258029,0.0002470013,0.00001008324,0.000005589564],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1691464,"threshold_uncertainty_score":0.4254609,"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."}}