{"id":"W1984266733","doi":"10.1016/s0168-8510(02)00198-7","title":"Setting priorities and allocating resources in health regions: lessons from a project evaluating program budgeting and marginal analysis (PBMA)","year":2003,"lang":"en","type":"article","venue":"Health Policy","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":103,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Canadian Health Services Research Foundation","keywords":"Context (archaeology); Health care; Management science; Operations research; Process management; Psychology; Political science; Business; Economics; Geography; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":["metaresearch","metaepi_narrow"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.03465037,0.0002926768,0.001514893,0.001484016,0.0008132943,0.000231065,0.0001508349,0.0001385965,0.00001773786],"category_scores_gemma":[0.009794159,0.0003801443,0.0001090166,0.001227902,0.0001275337,0.0003381253,0.00007876571,0.0003945345,0.00001432544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001084662,"about_ca_system_score_gemma":0.001511441,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1150159,"about_ca_topic_score_gemma":0.007691429,"domain_scores_codex":[0.9909354,0.002254222,0.004594916,0.0009786646,0.00016292,0.001073903],"domain_scores_gemma":[0.9938129,0.00190655,0.003419684,0.0004384534,0.00005605607,0.00036638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003009778,0.0002188962,0.646035,0.004492397,0.0004114368,0.000002408811,0.105056,0.0004254128,0.00000176768,0.2086767,0.001956428,0.03269342],"study_design_scores_gemma":[0.005112964,0.001262395,0.6205176,0.0031516,0.00008387776,0.00005355355,0.07661998,0.09584849,0.000001514538,0.04842051,0.1469651,0.001962432],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7078986,0.02920018,0.0008443053,0.2572856,0.0001126176,0.00289445,0.0002890781,0.000169837,0.001305337],"genre_scores_gemma":[0.8609697,0.002885312,0.1043288,0.03005978,0.0006223475,0.0006902363,0.00009000434,0.00009050265,0.0002633523],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2272258,"threshold_uncertainty_score":0.9998651,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4137127543368257,"score_gpt":0.5477993304531483,"score_spread":0.1340865761163226,"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."}}