{"id":"W4407301437","doi":"10.1007/s44250-025-00178-x","title":"Anticipated need, demand, and supply of doctors and beds in China: approaching a turning point","year":2025,"lang":"en","type":"article","venue":"Discover Health Systems","topic":"Healthcare Systems and Reforms","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Health Commission of the People's Republic of China","keywords":"Turning point; China; Point (geometry); Supply and demand; Natural resource economics; Business; Economics; Geography; Macroeconomics","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":[0.00206623,0.0001725998,0.0008926911,0.0005038101,0.0001248126,0.00007255546,0.00008782162,0.0001305521,0.000002425895],"category_scores_gemma":[0.00007541203,0.0001445727,0.0000456932,0.0003847712,0.00004993844,0.0002270243,0.00006762065,0.0002262382,0.000002259269],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001502584,"about_ca_system_score_gemma":0.0001083977,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09074384,"about_ca_topic_score_gemma":0.0005899483,"domain_scores_codex":[0.9976469,0.00008838006,0.001413824,0.0003888723,0.00004806309,0.0004139736],"domain_scores_gemma":[0.9990656,0.00003809627,0.0005282282,0.0002183398,0.00001502527,0.0001347526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001815413,0.00004179161,0.9355754,0.003923429,0.00003359067,0.000002189732,0.005382061,0.0001560338,0.000006937985,0.05381927,0.00005155566,0.0009895531],"study_design_scores_gemma":[0.001107891,0.0001282644,0.9814992,0.001767673,0.000002339603,0.00001542387,0.003525714,0.009156893,0.000004914143,0.0009323071,0.001627757,0.000231604],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.973716,0.02104229,0.001268747,0.001021334,0.0006315598,0.0007685056,0.00009847889,0.00001748689,0.001435639],"genre_scores_gemma":[0.9987072,0.0007560866,0.00004229856,0.0001323231,0.00004740845,0.00003822775,0.00001288509,0.00001642313,0.0002471535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09015389,"threshold_uncertainty_score":0.915311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02157126732810184,"score_gpt":0.27231219148172,"score_spread":0.2507409241536181,"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."}}