{"id":"W2124896831","doi":"","title":"Global age-friendly cities","year":2007,"lang":"en","type":"article","venue":"","topic":"Migration, Aging, and Tourism Studies","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geography; Economic growth; Population; Urbanization; Socioeconomics; Political science; Sociology; Demography","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":[0.001256245,0.001510841,0.0003673314,0.001191223,0.004018365,0.007187933,0.001244194,0.001951547,0.05732558],"category_scores_gemma":[0.001552893,0.0003691342,0.0005716144,0.003245055,0.001559139,0.003698373,0.01050497,0.001964602,0.02368543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002962708,"about_ca_system_score_gemma":0.009623376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01729581,"about_ca_topic_score_gemma":0.05349832,"domain_scores_codex":[0.9988623,0.0002203563,0.00004873481,0.0001405806,0.0002330718,0.000495115],"domain_scores_gemma":[0.9981444,0.00004437207,0.0001232151,0.0001517223,0.0005599661,0.0009763506],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00005483427,0.00007871639,0.008009118,0.0006044044,0.00001662268,0.0006057607,0.007170081,0.0004169143,0.0007035215,0.06274246,0.7956958,0.1239019],"study_design_scores_gemma":[0.000003983619,0.000009648529,0.00223717,0.00005356714,0.00000229425,0.00007993349,0.001393356,0.00001507206,0.00004580346,0.0006978811,0.9954548,0.000006438914],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03152118,0.01067241,0.004248902,0.02518401,0.006773399,0.0006202983,0.007055957,0.00201595,0.9119079],"genre_scores_gemma":[0.173272,0.01723211,0.02304408,0.01988553,0.001259562,0.001097087,0.0132155,0.001306786,0.7496873],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05732558,"threshold_uncertainty_score":0.1917731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01600733416447439,"score_gpt":0.3131049107152842,"score_spread":0.2970975765508099,"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."}}