{"id":"W7096949966","doi":"","title":"Population and Migration Trends in the District Differ from Nation’s","year":2013,"lang":"en","type":"article","venue":"","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Memphis; Productivity; Population; Population growth; Population density; Quarter (Canadian coin); Census; Metropolitan area","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":[0.00007862353,0.0001103477,0.0001174676,0.000800057,0.0005450272,0.0008361931,0.0003170877,0.0001340286,0.007288049],"category_scores_gemma":[0.000563005,0.00009719953,0.000129273,0.001682944,0.000209056,0.0003785769,0.0004189103,0.0003191756,0.0011525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001285658,"about_ca_system_score_gemma":0.0009956231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1249774,"about_ca_topic_score_gemma":0.3861677,"domain_scores_codex":[0.9998622,0.00001922738,0.000007440849,0.00002938756,0.00002353095,0.00005834068],"domain_scores_gemma":[0.9996293,0.00003878432,0.0001066049,0.00002178045,0.0001286139,0.00007487389],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006226393,0.00006707203,0.9666851,0.00004640731,0.0000508386,0.0001808049,0.001637897,0.0005588773,0.0009608087,0.002194394,0.01053821,0.01701744],"study_design_scores_gemma":[0.000003018842,0.00002135526,0.9787456,0.00001322995,0.000009265404,0.0001473875,0.002814279,0.0004571707,0.0002592293,0.0001068821,0.01741468,0.000007990218],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.974811,0.0001948108,0.0003556855,0.0005160316,0.00001693534,0.00002418281,0.0088205,0.0000385957,0.0152224],"genre_scores_gemma":[0.9824893,0.0001435508,0.0003788176,0.00009143424,0.000008339903,0.00002447016,0.004669742,0.000008542345,0.01218578],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1249774,"threshold_uncertainty_score":0.2485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02760777524009032,"score_gpt":0.1942936784855909,"score_spread":0.1666859032455006,"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."}}