{"id":"W2184963911","doi":"","title":"Input Data Warehousing: Canada's Experience with Establishment Level Information","year":2007,"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":"Data warehouse; Metadata; Business statistics; Computer science; Summary statistics; Database; Survey data collection; Data science; Business; Statistics; World Wide Web; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01083197,0.0008133987,0.0006564307,0.005175817,0.009003106,0.01566328,0.004085574,0.001460917,0.005902009],"category_scores_gemma":[0.01963335,0.0008756462,0.000908588,0.0308975,0.00487555,0.006360574,0.004801215,0.002929253,0.001240662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07343271,"about_ca_system_score_gemma":0.224128,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9902255,"about_ca_topic_score_gemma":0.9898018,"domain_scores_codex":[0.9863521,0.001342167,0.0005921798,0.001017864,0.008507188,0.002188511],"domain_scores_gemma":[0.960926,0.005456693,0.0009500862,0.003200471,0.02473056,0.004736124],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002006715,0.0003134844,0.02999292,0.001139623,0.0001251996,0.0007875002,0.01799608,0.00608405,0.002640754,0.07960311,0.2037517,0.6573649],"study_design_scores_gemma":[0.00004497785,0.00008646259,0.03385486,0.0008444809,0.00006272867,0.0004444238,0.01069646,0.006943593,0.002949313,0.007294326,0.9366078,0.0001705654],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1840311,0.04119533,0.156217,0.1493805,0.001882712,0.001445553,0.02045019,0.008823846,0.4365739],"genre_scores_gemma":[0.5143595,0.06208498,0.2883428,0.00686826,0.0004948924,0.0002968352,0.0242651,0.002136239,0.1011515],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.07343271,"threshold_uncertainty_score":0.5327941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1362543902991132,"score_gpt":0.3409747479705239,"score_spread":0.2047203576714107,"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."}}