{"id":"W3169000759","doi":"","title":"Use of a Depriviation Index in Analysing Health Disparities in Quebec, Canada","year":2006,"lang":"en","type":"article","venue":"","topic":"Global Health Care Issues","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Population; Index (typography); Geography; Demographic economics; Demography; Per capita; Public health; Socioeconomics; Economics; Sociology; Medicine","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":[0.003312911,0.0004273401,0.0004867456,0.005259443,0.003015776,0.001578768,0.001542579,0.0003648816,0.003695313],"category_scores_gemma":[0.006874884,0.0001513617,0.0007722757,0.009748613,0.0008316792,0.000448103,0.001213008,0.0006198534,0.0002004084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03758677,"about_ca_system_score_gemma":0.04769408,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9955304,"about_ca_topic_score_gemma":0.9963802,"domain_scores_codex":[0.9984044,0.0002981964,0.0001114276,0.0001848773,0.0006602332,0.0003409503],"domain_scores_gemma":[0.995923,0.0004816779,0.0004677165,0.0001669971,0.002411847,0.0005486686],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001617947,0.00003413268,0.9623935,0.0001482988,0.0001642635,0.00009657916,0.0008854461,0.0009564519,0.0002535818,0.001486252,0.006374188,0.02704555],"study_design_scores_gemma":[0.00001467227,0.00004297799,0.9917189,0.00009522533,0.00006430763,0.00003599695,0.001103519,0.001589606,0.0001518975,0.0001958475,0.004970108,0.00001706243],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.922422,0.002784289,0.005430429,0.002000043,0.00008455356,0.001043281,0.03991604,0.0001632485,0.02615602],"genre_scores_gemma":[0.9839872,0.0004722232,0.005526006,0.000218703,0.00001272824,0.000459945,0.006112052,0.00002600026,0.003185093],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03758677,"threshold_uncertainty_score":0.2727125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04851058033234138,"score_gpt":0.394341222604519,"score_spread":0.3458306422721776,"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."}}