{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002893334,0.00008212569,0.00007897381,0.00004691977,0.00009248952,0.00004732544,0.0001682391,0.00002678048,0.0001010899],"category_scores_gemma":[0.0001592641,0.00006236715,0.000005239144,0.0001457245,0.00001426687,0.0008769356,0.00006345852,0.00004856742,0.000003926418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001228351,"about_ca_system_score_gemma":0.0001810684,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1573384,"about_ca_topic_score_gemma":0.6331701,"domain_scores_codex":[0.9990913,0.000006423853,0.0002812651,0.00009864476,0.0003632015,0.0001592061],"domain_scores_gemma":[0.9991768,0.00008530272,0.0001185352,0.0004457677,0.0001096317,0.0000639455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002969815,0.0003268674,0.1769078,0.000448418,0.00009341656,0.00003902771,0.01972967,0.001699859,0.0001125658,0.2624545,0.2544897,0.2834011],"study_design_scores_gemma":[0.002441806,0.0001394753,0.3970806,0.0001996884,0.0000790124,0.0001238275,0.007505056,0.07680191,0.004213545,0.004792614,0.5052225,0.001399942],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3407253,0.000004043407,0.6436552,0.0005007145,0.0001655702,0.0002728286,0.00005326442,0.00009793344,0.01452507],"genre_scores_gemma":[0.9413488,6.158576e-7,0.05782355,0.000332599,0.00002831813,0.000002264979,0.0002328486,0.000006057818,0.0002249395],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6006235,"threshold_uncertainty_score":0.8482729,"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."}}