{"id":"W2170589938","doi":"10.2105/ajph.93.3.388","title":"Evolution of the Determinants of Health, Health Policy, and Health Information Systems in Canada","year":2003,"lang":"en","type":"article","venue":"American Journal of Public Health","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"Baycrest Hospital","funders":"","keywords":"Health promotion; Public health; Health policy; Health equity; Population health; Socioeconomic status; Health care; Social determinants of health; Government (linguistics); Environmental health; Population; Inequality; Economic growth; HRHIS; International health; Political science; Medicine; Nursing; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01486453,0.0001155055,0.0009539236,0.0003582083,0.0004710078,0.00003021673,0.0002674829,0.0000298366,0.000003497098],"category_scores_gemma":[0.001023787,0.00008997569,0.0000589474,0.001274907,0.0002887221,0.0004590511,0.00002253171,0.0002638514,1.615608e-7],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.008058535,"about_ca_system_score_gemma":0.1640056,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9976627,"about_ca_topic_score_gemma":0.9740129,"domain_scores_codex":[0.9920411,0.003518441,0.002435638,0.00009972273,0.0008829109,0.001022231],"domain_scores_gemma":[0.9934429,0.0002328393,0.004991524,0.0001771782,0.0002672797,0.0008882695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000005372503,0.00004527788,0.7620304,0.0008765623,0.000008146895,2.505784e-7,0.01700787,0.00004712393,2.464186e-8,0.03497301,0.001670479,0.1833355],"study_design_scores_gemma":[0.0004398139,0.0005377592,0.8295151,0.0005212766,8.76729e-7,0.00002634987,0.1032397,0.00005427101,2.073651e-7,0.00009610361,0.06548784,0.00008064806],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6679062,0.008194186,0.0005022191,0.3208363,0.001211058,0.0009359997,0.00006397338,0.000007362683,0.0003426511],"genre_scores_gemma":[0.9851967,0.003153454,0.0001682013,0.01139626,0.00006520996,0.000002820833,7.389536e-7,0.000006600022,0.000009989838],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3172905,"threshold_uncertainty_score":0.9957494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03837446570011503,"score_gpt":0.3567542150033782,"score_spread":0.3183797493032631,"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."}}