{"id":"W2044006221","doi":"10.1007/s12126-009-9036-5","title":"Information Provision for an Age-Friendly Community","year":2009,"lang":"en","type":"article","venue":"Ageing International","topic":"Technology Use by Older Adults","field":"Social Sciences","cited_by":39,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Australian Government; Australian Research Council; AGE-WELL","keywords":"Inclusion (mineral); Government (linguistics); Public relations; Action (physics); Order (exchange); Community education; Business; Information Dissemination; Service (business); Local government; Political science; Economic growth; Psychology; Public administration; Marketing; Computer science; World Wide Web; Social psychology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000549202,0.00005368127,0.000053434,0.0001111641,0.0005295616,0.0001172393,0.0004775671,0.00008638405,0.00002251332],"category_scores_gemma":[0.0006527014,0.00005675439,0.00003112566,0.00008355519,0.00007831491,0.001281048,0.00002794252,0.0001615353,0.00002120819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009460541,"about_ca_system_score_gemma":0.0000452387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009902718,"about_ca_topic_score_gemma":0.001555703,"domain_scores_codex":[0.9993555,0.00007265346,0.0001458268,0.00005566481,0.0002293714,0.0001409805],"domain_scores_gemma":[0.9995061,0.00007386343,0.00007924825,0.0001357684,0.0001657493,0.00003922929],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006021006,0.000243883,0.001197931,0.000006521482,0.00002327946,0.000004471373,0.06483546,0.0000464462,0.000716402,0.304117,0.01049217,0.6182563],"study_design_scores_gemma":[0.001314077,0.0006312563,0.1039588,0.00006367642,0.0000120622,0.000003786112,0.01514401,0.001530389,0.0006280136,0.08921496,0.7871765,0.0003224406],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9158055,0.00000420212,0.01906769,0.007114227,0.0006476853,0.0004359687,0.00001810958,0.0005047312,0.05640185],"genre_scores_gemma":[0.9951499,0.000003590405,0.003697505,0.0006261865,0.0001137869,0.0000144997,0.0001005449,0.000002747331,0.0002912821],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7766843,"threshold_uncertainty_score":0.4073013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02581766341255107,"score_gpt":0.3347419304740852,"score_spread":0.3089242670615342,"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."}}