{"id":"W4309457649","doi":"10.5195/aa.2022.391","title":"Ageing in Space: Remaking Community for Older Adults","year":2022,"lang":"en","type":"article","venue":"Anthropology & Aging","topic":"Migration, Aging, and Tourism Studies","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University","funders":"York University","keywords":"Sociology; Context (archaeology); Everyday life; Space (punctuation); Diversity (politics); Divergence (linguistics); Social space; Social relation; Gender studies; Population ageing; Population; Public relations; Political science; Social science; Geography; Anthropology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003185096,0.0003950144,0.0003518615,0.001263738,0.01322948,0.005241114,0.001546093,0.002341694,0.003428516],"category_scores_gemma":[0.003989924,0.0002417649,0.0003428148,0.0009154389,0.01333673,0.006617298,0.01218755,0.0020137,0.0003493993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003865954,"about_ca_system_score_gemma":0.007634464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.043725,"about_ca_topic_score_gemma":0.1243033,"domain_scores_codex":[0.9974648,0.001461814,0.00009307043,0.0002019794,0.0002496401,0.0005287057],"domain_scores_gemma":[0.997709,0.0004165839,0.0003084711,0.0001255727,0.000345159,0.00109517],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001615708,0.00003395091,0.004675435,0.0001389769,0.000003714458,0.0007123817,0.9619155,0.00002911554,0.0004116255,0.0109358,0.00233855,0.01878884],"study_design_scores_gemma":[0.000004228345,0.00005285682,0.003759648,0.0001899682,0.000005562695,0.0002887295,0.9405456,0.00004001426,0.00006084421,0.002870081,0.05217001,0.00001233508],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9119203,0.006236546,0.003999999,0.02106582,0.0007721955,0.000163345,0.00005050217,0.00005013339,0.05574116],"genre_scores_gemma":[0.9909196,0.001540583,0.001532304,0.001033791,0.00008615763,0.00005654257,0.00002152591,0.00001376274,0.00479578],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.043725,"threshold_uncertainty_score":0.08694094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02285891584083447,"score_gpt":0.3496324678555879,"score_spread":0.3267735520147534,"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."}}