{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.002431131,0.001111007,0.00295229,0.000498556,0.0009098728,0.0005701046,0.0009184118,0.0006109545,0.0005586739],"category_scores_gemma":[0.001353605,0.001079595,0.000304859,0.001469158,0.006309431,0.0004606914,0.0005118126,0.001898622,0.00001299333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00160643,"about_ca_system_score_gemma":0.002004682,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.07059803,"about_ca_topic_score_gemma":0.02099559,"domain_scores_codex":[0.9917076,0.002232988,0.002080054,0.001174417,0.0006085563,0.002196355],"domain_scores_gemma":[0.9943185,0.001979597,0.0007192264,0.002045548,0.000249613,0.0006875304],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001173484,0.001241702,0.8493212,0.007294375,0.0003448209,0.0004536405,0.02454582,0.000006087624,0.00001908778,0.01179153,0.007809737,0.09599853],"study_design_scores_gemma":[0.005322543,0.002465085,0.7535782,0.003332534,0.001000778,0.0000933282,0.1313195,0.0006308097,0.00003336745,0.001442561,0.09918448,0.001596825],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9207091,0.05328106,0.0008771449,0.002545104,0.000666832,0.003065301,0.0001428821,0.0003546604,0.01835786],"genre_scores_gemma":[0.9829327,0.008393073,0.002554045,0.002372771,0.0002233717,0.0005934944,0.0001526098,0.00007007508,0.002707786],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1067737,"threshold_uncertainty_score":0.9991654,"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."}}