{"id":"W4390942978","doi":"10.35483/acsa.am.110.86","title":"Mixing Metabolisms: New People in Aging Sprawl","year":2022,"lang":"en","type":"article","venue":"","topic":"Migration, Ethnicity, and Economy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Urban sprawl; Ethnic group; Immigration; Human settlement; Economic geography; Settlement (finance); Built environment; Political science; Geography; Urban planning; Economic growth; Sociology; Business; Engineering; Civil engineering; Economics","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":[0.001762227,0.0003316787,0.0002855291,0.001131308,0.007206536,0.006442187,0.0006014391,0.001567836,0.003303276],"category_scores_gemma":[0.00178406,0.0002421208,0.0002581878,0.0007915078,0.007977811,0.005898731,0.005079673,0.002308275,0.000249593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002286465,"about_ca_system_score_gemma":0.001986837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01725222,"about_ca_topic_score_gemma":0.0383185,"domain_scores_codex":[0.9992131,0.0003970205,0.00002794394,0.00008568299,0.000116855,0.0001592932],"domain_scores_gemma":[0.9993229,0.0001838384,0.0001279795,0.00003781069,0.00007927157,0.0002483137],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004375635,0.000138391,0.01855671,0.00009423795,0.00001584354,0.0008878204,0.8812649,0.00005604588,0.0004074062,0.04827981,0.008022871,0.04223233],"study_design_scores_gemma":[0.00001056396,0.00008355718,0.01838186,0.0001914559,0.00002926165,0.0007645681,0.8344715,0.0001283125,0.0001743196,0.01249297,0.1332408,0.0000308268],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.8404889,0.01573719,0.001505659,0.0458549,0.00124013,0.00004156414,0.00006915003,0.00005040757,0.09501217],"genre_scores_gemma":[0.9839588,0.004467537,0.0004307225,0.002355592,0.0002449179,0.00001973495,0.00001991775,0.0000144938,0.008488355],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01725222,"threshold_uncertainty_score":0.03430355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02554924087657035,"score_gpt":0.2927302116979285,"score_spread":0.2671809708213582,"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."}}