{"id":"W4390906082","doi":"10.5070/t5.1868","title":"Access Statistics Canada’s Open Economic Data for Statistics and Data Science Courses","year":2024,"lang":"en","type":"article","venue":"Technology Innovations in Statistics Education","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Center for Interuniversity Research and Analysis on Organizations; HEC Montréal","funders":"","keywords":"Economic statistics; Open data; Statistics; Business statistics; Official statistics; Government (linguistics); Economic data; Statistics education; Summary statistics; Computer science; Data access; Data science; Database; Mathematics; World Wide Web","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":[0.00922438,0.001348471,0.001642526,0.01533756,0.005045373,0.008400652,0.003682368,0.002430944,0.2383234],"category_scores_gemma":[0.09726422,0.00137879,0.001499878,0.02497236,0.00162474,0.003767801,0.004731292,0.003393392,0.1062906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0369682,"about_ca_system_score_gemma":0.2229722,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9531493,"about_ca_topic_score_gemma":0.9624704,"domain_scores_codex":[0.981407,0.001461596,0.001002103,0.001140537,0.01233806,0.0026506],"domain_scores_gemma":[0.8465779,0.01842772,0.003694092,0.01433389,0.1013093,0.01565717],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002322437,0.00002023368,0.001716203,0.00009084481,0.00001423087,0.00002785324,0.00007339045,0.0001625926,0.00005639984,0.004200532,0.974951,0.01866357],"study_design_scores_gemma":[0.00004561346,0.000006248421,0.006249047,0.0001814476,0.00001298695,0.00002313646,0.0001916569,0.0007181094,0.0002581407,0.003426993,0.98881,0.00007660272],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.001406189,0.0002739718,0.008174454,0.01109716,0.0007083399,0.0006948338,0.8043575,0.01142166,0.1618659],"genre_scores_gemma":[0.02972658,0.001564349,0.05627697,0.008749784,0.0004866655,0.002134513,0.7069404,0.01380081,0.1803199],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2383234,"threshold_uncertainty_score":0.7972711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08726829237015858,"score_gpt":0.4494758471171822,"score_spread":0.3622075547470236,"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."}}