{"id":"W2149793156","doi":"10.1186/1476-072x-3-5","title":"Accuracy of city postal code coordinates as a proxy for location of residence","year":2004,"lang":"en","type":"article","venue":"International Journal of Health Geographics","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":99,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Eli Lilly Canada; Government of Canada; Boston Scientific Corporation; Fondation pour la Recherche Médicale; Eli Lilly and Company","keywords":"Residence; Proxy (statistics); Geocoding; Geography; Computer science; Zip code; Statistic; Geographic information system; Code (set theory); Database; Statistics; Cartography; Demography; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.001157349,0.00009927534,0.0003805595,0.0004244095,0.00003563174,0.00001036708,0.0003032036,0.00005150964,0.0000141194],"category_scores_gemma":[0.002794469,0.00008861125,0.0001679284,0.00034034,0.0001499231,0.0002200354,0.00003979945,0.0001803082,9.840791e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001119684,"about_ca_system_score_gemma":0.001837159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003545131,"about_ca_topic_score_gemma":0.00006201353,"domain_scores_codex":[0.9978034,0.00005454884,0.001072286,0.0001273426,0.0007855481,0.0001568951],"domain_scores_gemma":[0.9929718,0.0002941915,0.001754287,0.0001704189,0.004669832,0.0001394803],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.007799614,0.002422972,0.9375445,0.002361636,0.001108721,0.000107291,0.001116349,0.001249027,0.00306189,0.01754777,0.002235756,0.02344451],"study_design_scores_gemma":[0.008933578,0.003569398,0.9499568,0.005437241,0.0001179599,0.0007317773,0.0004752857,0.0002585863,0.007176226,0.01946128,0.003674237,0.0002075889],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9702244,0.003652687,0.008931252,0.01571267,0.0004870888,0.0005640588,0.0003685303,0.0000140307,0.00004525697],"genre_scores_gemma":[0.9940302,0.001009308,0.004133312,0.0006197729,0.000111521,0.00000543229,0.00007020163,0.00001135814,0.000008863053],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02380581,"threshold_uncertainty_score":0.3613462,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02922790333932,"score_gpt":0.3857384606297455,"score_spread":0.3565105572904255,"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."}}