{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001401107,0.00009344672,0.0001848899,0.0001320059,0.005442314,0.00002410983,0.000231978,0.00004207454,0.0003587009],"category_scores_gemma":[0.0002020875,0.0001061116,0.0000561091,0.0002790968,0.0005299133,0.0001177143,0.0001725761,0.0003685471,0.000002111282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001440902,"about_ca_system_score_gemma":0.00008037501,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2201525,"about_ca_topic_score_gemma":0.2401992,"domain_scores_codex":[0.9983612,0.0007033329,0.0001837492,0.0001845703,0.0001570315,0.0004100828],"domain_scores_gemma":[0.9992352,0.0004248366,0.0001063075,0.0001565469,0.00004538093,0.00003178393],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00001423558,0.00008609542,0.03485111,0.00002295912,0.00001919851,0.0000217193,0.9449401,0.00002821919,0.0000204717,0.01158455,0.003699209,0.004712063],"study_design_scores_gemma":[0.001818091,0.0001421977,0.2330979,0.0001351823,0.00004431724,0.000007731758,0.6505108,0.0002742587,0.0001419157,0.01241635,0.1008866,0.0005246879],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9881041,0.0007074144,0.000484584,0.006524871,0.0007635741,0.0003055203,0.000005436926,0.00008282734,0.003021661],"genre_scores_gemma":[0.9982759,0.0001544247,0.0003504461,0.0004327014,0.0001997993,0.0000781582,0.000008852679,0.0000119405,0.0004877728],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2944293,"threshold_uncertainty_score":0.9958525,"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."}}