{"id":"W4417188341","doi":"10.61415/riage.413","title":"AGE-FRIENDLY CITIES AND COMMUNITIES PROGRAM: SUCCESS STORIES IN PARANÁ/BRAZIL","year":2025,"lang":"","type":"article","venue":"RIAGE - Revista Ibero-Americana de Gerontologia","topic":"Aging, Health, and Disability","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Outreach; Certification; State (computer science); Population; Action (physics); Capacity building","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":[0.003162732,0.0002948506,0.0002660544,0.0004455351,0.006757281,0.002312529,0.0008731139,0.0007450525,0.001925272],"category_scores_gemma":[0.005772948,0.0002432516,0.0003086998,0.0007403779,0.002258724,0.00229343,0.006806033,0.001911491,0.0001911595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004188381,"about_ca_system_score_gemma":0.01010533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08171208,"about_ca_topic_score_gemma":0.2216811,"domain_scores_codex":[0.9981459,0.000963159,0.0000573183,0.000101779,0.0002517048,0.0004801496],"domain_scores_gemma":[0.9972494,0.0004762331,0.000275925,0.0001125261,0.0003480217,0.001537903],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001110925,0.0006565101,0.09564327,0.0009370006,0.00006282471,0.004646081,0.6317223,0.0003218475,0.001553946,0.03335405,0.06464056,0.1663505],"study_design_scores_gemma":[0.00002878302,0.0002241427,0.06876928,0.001040976,0.00004332955,0.001266974,0.6460624,0.0003651448,0.000591788,0.002772504,0.2787725,0.00006222881],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8972719,0.002985843,0.0006914779,0.05670416,0.0004580654,0.0001979681,0.000336085,0.00007096068,0.0412835],"genre_scores_gemma":[0.9842677,0.004127277,0.0009305931,0.003782376,0.00005971974,0.0001457571,0.000165055,0.00004714453,0.006474373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08171208,"threshold_uncertainty_score":0.1624729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02689950344970812,"score_gpt":0.3593832350015406,"score_spread":0.3324837315518325,"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."}}