{"id":"W6922047674","doi":"10.11575/prism/42531","title":"Impact of Aging Population on Healthcare Financing Needs in Canada","year":2023,"lang":"en","type":"other","venue":"Open MIND","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Health care; Government (linguistics); Population ageing; Per capita; Population; Demographics; Healthcare delivery","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001130235,0.0002733362,0.0003037485,0.002679449,0.003259766,0.003924119,0.001132415,0.0006639542,0.007086628],"category_scores_gemma":[0.0077299,0.0001964867,0.0006594386,0.004536952,0.0007313361,0.001088912,0.001577793,0.0009754016,0.0003165555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1001629,"about_ca_system_score_gemma":0.1967197,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9974154,"about_ca_topic_score_gemma":0.9984041,"domain_scores_codex":[0.9976986,0.0001123734,0.00007107756,0.00007050863,0.0007550339,0.001292399],"domain_scores_gemma":[0.9940934,0.0004339698,0.0004905559,0.00007050695,0.003058089,0.001853418],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001738621,0.00009642198,0.6062596,0.0004518089,0.0001630475,0.001201928,0.002643676,0.004154298,0.0002571993,0.04709342,0.234114,0.1033908],"study_design_scores_gemma":[0.00004410607,0.00003299545,0.8271176,0.0007977294,0.0001189079,0.0003335088,0.008352366,0.004948699,0.0004106535,0.003351259,0.1543862,0.0001059246],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6397321,0.01066553,0.0005148774,0.1175766,0.0004828939,0.0002989805,0.05483799,0.0001992494,0.1756918],"genre_scores_gemma":[0.958784,0.007575157,0.001091726,0.00545775,0.0001326217,0.00008459672,0.009784693,0.00004246069,0.01704708],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1001629,"threshold_uncertainty_score":0.7267362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05010959094150014,"score_gpt":0.3606861353173627,"score_spread":0.3105765443758626,"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."}}