{"id":"W2146612649","doi":"","title":"Metadata and controlled vocabularies in the government of Canada: a situational analysis","year":2004,"lang":"en","type":"article","venue":"International Conference on Dublin Core and Metadata Applications","topic":"E-Government and Public Services","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Government of Canada","funders":"","keywords":"Metadata; Controlled vocabulary; Interoperability; Computer science; World Wide Web; Government (linguistics); Meta Data Services; Geospatial metadata; Data element; Cataloging; Metadata repository; Knowledge management","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":[0.0008505561,0.00009056797,0.0002065596,0.00007658413,0.0001913749,0.0002822157,0.0005094353,0.00003775161,0.0001257295],"category_scores_gemma":[0.0001695558,0.00006739414,0.00003744466,0.0003653608,0.000196217,0.0005166437,0.00006688158,0.00008828125,3.891578e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009901547,"about_ca_system_score_gemma":0.0005746105,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.118005,"about_ca_topic_score_gemma":0.7052812,"domain_scores_codex":[0.9981649,0.00006262616,0.0002737882,0.00022072,0.001157708,0.0001202384],"domain_scores_gemma":[0.9990159,0.000386975,0.000180078,0.0002089394,0.0001524419,0.00005570606],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004391639,0.00007311447,0.002615209,0.00000253426,0.0002213712,6.048258e-7,0.0008029121,0.0000219162,0.00003528995,0.9952664,0.00009174194,0.0008249977],"study_design_scores_gemma":[0.01175283,0.0001700376,0.2187408,0.00009781015,0.002220762,0.000006262326,0.09565937,0.006133953,0.0002913986,0.2304551,0.433439,0.001032744],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5769068,0.001127481,0.03814087,0.2326662,0.0003080107,0.003215986,0.003198239,0.00004245483,0.144394],"genre_scores_gemma":[0.9971812,0.0003973586,0.0003956114,0.0007617911,0.00005304013,0.0001739017,0.0001525765,0.000002458202,0.0008820873],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7648113,"threshold_uncertainty_score":0.8878683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0627694684407773,"score_gpt":0.3278424819088162,"score_spread":0.2650730134680389,"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."}}