{"id":"W1988424043","doi":"10.1007/s12546-013-9118-9","title":"Estimating historic population data for small geographies using census housing information","year":2013,"lang":"en","type":"article","venue":"Journal of Population Research","topic":"Urban, Neighborhood, and Segregation Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Census; Population; Unit (ring theory); Census tract; Geography; Quarter (Canadian coin); Sample (material); Estimation; Demography; Population statistics; Demographic analysis; Statistics; Sociology; Mathematics; Economics; Archaeology","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003823139,0.00008946222,0.0002082232,0.0008337022,0.001609374,0.0003726791,0.0003537864,0.00009602035,0.00003420155],"category_scores_gemma":[0.003928998,0.00008141048,0.00007117035,0.0008023367,0.0000852143,0.002870986,0.00008813392,0.00023328,0.000004847804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003934469,"about_ca_system_score_gemma":0.0001100129,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02268451,"about_ca_topic_score_gemma":0.001309599,"domain_scores_codex":[0.9974285,0.0003358982,0.0007328726,0.000122455,0.001030589,0.0003496719],"domain_scores_gemma":[0.9964015,0.0005645282,0.0006416808,0.0002121386,0.002063764,0.0001163896],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001209147,0.0001320721,0.7903783,0.0002242968,0.0001506326,0.000002129515,0.01423049,0.01264791,0.0001402253,0.009490807,0.02012836,0.1523539],"study_design_scores_gemma":[0.001373281,0.00018045,0.582524,0.0002976636,0.0001008959,0.000007675192,0.01563666,0.3409364,0.000005790009,0.02119064,0.03730543,0.0004411262],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9675562,0.0004060827,0.0276534,0.0016559,0.001350228,0.00082083,0.00002598447,0.00003968675,0.000491728],"genre_scores_gemma":[0.9510853,0.0000465695,0.04766239,0.00002810318,0.0009753964,0.000006820498,0.0001091154,0.0000105466,0.00007570652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3282884,"threshold_uncertainty_score":0.9996904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3402968571442207,"score_gpt":0.4598096388708803,"score_spread":0.1195127817266596,"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."}}