{"id":"W2966783508","doi":"10.29173/cais1111","title":"Canada’s Health Data Repositories: Challenges of Organization, Discoverability and Access","year":2019,"lang":"en","type":"article","venue":"Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"University of Alberta","keywords":"Discoverability; Metadata; Interoperability; Open data; Health data; World Wide Web; Computer science; Institutional repository; Linked data; Data science; Health care; Political science; Semantic Web","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.06802972,0.0007229167,0.001703196,0.01807642,0.01086891,0.02776412,0.008288085,0.002613935,0.003537495],"category_scores_gemma":[0.1631589,0.0009475409,0.001792049,0.03823815,0.009885949,0.0197894,0.01521294,0.003977518,0.00117323],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06836314,"about_ca_system_score_gemma":0.1921402,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8995988,"about_ca_topic_score_gemma":0.9100643,"domain_scores_codex":[0.9474993,0.01335387,0.004195708,0.003697073,0.02732975,0.003924343],"domain_scores_gemma":[0.6914277,0.1163181,0.01553129,0.04468922,0.1146741,0.01735966],"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":[0.0004903297,0.0002503512,0.05863323,0.002890393,0.0006090975,0.0005096206,0.01428234,0.005142072,0.002527049,0.250596,0.1648801,0.4991895],"study_design_scores_gemma":[0.0001501362,0.0001289443,0.0737556,0.004244389,0.0004142473,0.0005838788,0.02877131,0.01328602,0.003474736,0.1527213,0.7219124,0.0005571057],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1320338,0.0275357,0.1457757,0.5368851,0.001472222,0.001903192,0.0413795,0.004333736,0.108681],"genre_scores_gemma":[0.5052388,0.01914311,0.3873189,0.0207276,0.0008601955,0.001048071,0.04466121,0.001324461,0.01967768],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9722359,"threshold_uncertainty_score":0.4960117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03103120629131195,"score_gpt":0.2767233769537491,"score_spread":0.2456921706624371,"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."}}