{"id":"W2998326685","doi":"10.12927/hcpap.2019.26034","title":"Using Data to Move from Volume to Value","year":2019,"lang":"en","type":"article","venue":"A Nudge Too Far? A Nudge at All? On Paying People to Be Healthy","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Advancing Health Outcomes; Michael Smith Health Research BC","funders":"","keywords":"Health care; Value (mathematics); Volume (thermodynamics); Focus (optics); Healthcare delivery; Healthcare policy; Healthcare system; Business; Computer science; Health policy; Economics; Health care reform; Economic growth","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.01027021,0.0007284571,0.001242517,0.01273289,0.001400501,0.007146963,0.002390264,0.001399162,0.007528844],"category_scores_gemma":[0.1123713,0.0004729522,0.001011186,0.02933994,0.002005055,0.003367869,0.003460571,0.003604957,0.002105837],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01939769,"about_ca_system_score_gemma":0.01438488,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.8287753,"about_ca_topic_score_gemma":0.7275038,"domain_scores_codex":[0.9814415,0.003444316,0.001442978,0.002063588,0.01009559,0.001512102],"domain_scores_gemma":[0.9125606,0.03370627,0.01349538,0.007293563,0.03084496,0.002099138],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003555118,0.000176776,0.5044832,0.001304225,0.001293079,0.0002639335,0.002543657,0.01548453,0.0003832812,0.09750917,0.2753975,0.1008051],"study_design_scores_gemma":[0.0001136056,0.0001444288,0.4057235,0.001062778,0.0003499541,0.0001848407,0.004666978,0.01123584,0.001406209,0.05792853,0.5169194,0.0002640001],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.1368369,0.006179767,0.04078104,0.02595441,0.001819258,0.0008520494,0.6815519,0.001262862,0.1047619],"genre_scores_gemma":[0.6416435,0.002514301,0.02665828,0.004370749,0.0005890637,0.001418579,0.2995772,0.0004788826,0.0227495],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8287753,"threshold_uncertainty_score":0.344466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2201665951422745,"score_gpt":0.3501172902123845,"score_spread":0.12995069507011,"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."}}