{"id":"W4292458043","doi":"10.32388/9smv1e.2","title":"Building a digital republic to reduce health disparities and improve population health in the United States","year":2022,"lang":"en","type":"preprint","venue":"Qeios","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Poverty; Government (linguistics); Medicaid; Business; Work (physics); Population; Welfare; Economic growth; Social Welfare; Health care; Public economics; Political science; Medicine; Environmental health; Economics; Engineering","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":[0.006084246,0.0003308667,0.0003665532,0.002086284,0.002206889,0.004608949,0.0007363601,0.0009527103,0.01721434],"category_scores_gemma":[0.01383048,0.0002109132,0.0005111661,0.003331662,0.001679086,0.008196654,0.008110806,0.001699763,0.002493684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001468638,"about_ca_system_score_gemma":0.00603331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01313735,"about_ca_topic_score_gemma":0.01350561,"domain_scores_codex":[0.9985031,0.0007295926,0.00006413362,0.0001757249,0.0003249788,0.0002025148],"domain_scores_gemma":[0.9966355,0.0009806816,0.0002343028,0.0009880126,0.0005645524,0.0005969914],"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":[0.0001033381,0.0004325569,0.02931789,0.0002297176,0.00006929711,0.00006289759,0.002237132,0.001568904,0.000434596,0.1925322,0.2896934,0.4833181],"study_design_scores_gemma":[0.0001088531,0.000136269,0.03023317,0.0009761621,0.00009245806,0.00007454252,0.004663382,0.0057508,0.001442534,0.1750146,0.7814584,0.00004882989],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1417452,0.009079974,0.06977051,0.3051223,0.004719793,0.0006245496,0.01990425,0.003771213,0.445262],"genre_scores_gemma":[0.7363335,0.01811991,0.1270614,0.04163114,0.002476702,0.000930489,0.01790641,0.0007148906,0.05482559],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01721434,"threshold_uncertainty_score":0.05758768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04596884319460037,"score_gpt":0.3927620222807241,"score_spread":0.3467931790861237,"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."}}