{"id":"W2181728226","doi":"","title":"RECENT DEVELOPMENTS IN THE REDESIGN OF STATISTICS CANADA'S BUSINESS REGISTER","year":2006,"lang":"en","type":"article","venue":"","topic":"Census and Population Estimation","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Register (sociolinguistics); Business statistics; Computer science; Sampling frame; Statistics; Descriptive statistics; Sampling design; Frame (networking); Data science; Operations research; Engineering; Mathematics; Sociology; Telecommunications","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002008866,0.00004880454,0.00007658764,0.00002347177,0.0000232463,0.000006964347,0.00006122202,0.00001828969,0.00006081176],"category_scores_gemma":[0.0001356806,0.0000327345,0.000003729833,0.0001850956,0.000008863725,0.00001965786,0.000006510141,0.00002670921,7.350233e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006056815,"about_ca_system_score_gemma":0.0001627567,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.139552,"about_ca_topic_score_gemma":0.689403,"domain_scores_codex":[0.9993585,0.00003457278,0.0002760793,0.00005440096,0.0002013086,0.00007519085],"domain_scores_gemma":[0.9994919,0.0001521457,0.000098866,0.0001124237,0.0001375437,0.00000715307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00001729779,0.0001336523,0.03372112,0.0001109859,0.000006347691,0.000009595169,0.000283194,0.0003568524,0.00003571271,0.4974364,0.4512447,0.01664409],"study_design_scores_gemma":[0.0003303112,0.000005242429,0.876887,0.00003617266,0.00000981176,0.000005001908,0.00007145325,0.0007999914,0.0001518218,0.05433261,0.06725299,0.0001175422],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4214888,0.0001484888,0.357576,0.01015041,0.0008495967,0.002094179,0.0002459685,0.00008153833,0.207365],"genre_scores_gemma":[0.9088514,0.00001259514,0.08913203,0.0001829974,0.00002303265,0.000007404542,0.000106037,0.000008658018,0.001675842],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8431659,"threshold_uncertainty_score":0.8661778,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05997031826933358,"score_gpt":0.2915739410343421,"score_spread":0.2316036227650086,"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."}}