{"id":"W2561904393","doi":"10.1504/ijbhr.2016.10002014","title":"Application of the analytical hierarchy process to optimisation of healthcare financing","year":2016,"lang":"en","type":"article","venue":"International Journal of Behavioural and Healthcare Research","topic":"Healthcare Systems and Reforms","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Royal University","funders":"","keywords":"Analytic hierarchy process; Pace; Health care; Life expectancy; Business; Process (computing); Hierarchy; Expectancy theory; Economic growth; Finance; Economics; Computer science; Medicine; Management","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":[0.002192139,0.00007849325,0.0003273662,0.0004759226,0.00008928813,0.0000167077,0.0004317246,0.0001029839,0.00001250048],"category_scores_gemma":[0.0002758827,0.00004493343,0.000105214,0.0003227396,0.0001200207,0.0001703041,0.00009024558,0.0002910114,0.00000433663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002927652,"about_ca_system_score_gemma":0.0002576723,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007784706,"about_ca_topic_score_gemma":0.0002949426,"domain_scores_codex":[0.9978924,0.00008707681,0.001196604,0.0001768245,0.0004049712,0.0002420763],"domain_scores_gemma":[0.9971922,0.0000729323,0.0006655522,0.0001673474,0.001709332,0.0001926484],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001350133,0.00007563899,0.8456599,0.0001949597,0.00002889484,0.000003106529,0.001174624,0.00001196569,0.0002781969,0.04220118,0.0000438207,0.1101927],"study_design_scores_gemma":[0.0006982588,0.0006262591,0.9802347,0.0008550962,0.00000227113,0.00007616999,0.0006470499,0.0001766791,0.001216499,0.01383487,0.001520485,0.0001116736],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9113371,0.000685372,0.001088164,0.08610705,0.0003257888,0.000288136,0.0001081982,0.00000241799,0.00005773885],"genre_scores_gemma":[0.999145,0.0003062269,0.0001615639,0.0001070954,0.00014981,0.00001148869,0.000001500939,0.000009612229,0.0001077498],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1345748,"threshold_uncertainty_score":0.9988226,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1767326289620477,"score_gpt":0.4131246456661812,"score_spread":0.2363920167041335,"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."}}