{"id":"W2048393120","doi":"10.1300/j123v51n02_09","title":"Metadata, Contextual Data, and the Canadian Century Research Infrastructure","year":2006,"lang":"en","type":"article","venue":"The Serials Librarian","topic":"Data Analysis and Archiving","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadiana.org","funders":"","keywords":"Microdata (statistics); Metadata; Research data; Private sector; Library science; Social research; Census; Data science; Political science; World Wide Web; Computer science; Sociology; Social science; Data curation; Population","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01289752,0.0003241551,0.0004586484,0.01397241,0.01339797,0.0210194,0.002217609,0.0009296042,0.007338327],"category_scores_gemma":[0.03038445,0.0006245006,0.000321687,0.04754536,0.01206327,0.006564075,0.006732938,0.001768001,0.0006091598],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1198519,"about_ca_system_score_gemma":0.2140434,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9720427,"about_ca_topic_score_gemma":0.9774361,"domain_scores_codex":[0.9860685,0.003184461,0.0008928244,0.001043628,0.00725638,0.001554184],"domain_scores_gemma":[0.9668356,0.00800096,0.002288372,0.005128731,0.01570013,0.002046177],"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":[0.00005732137,0.0000317519,0.01949219,0.0004670261,0.0000417105,0.0001973058,0.02071114,0.001655655,0.0005647832,0.6900353,0.091876,0.1748697],"study_design_scores_gemma":[0.00001357625,0.00001217928,0.02087362,0.0009351216,0.00004066527,0.00008455171,0.02098443,0.00105076,0.0007743278,0.0437072,0.9114278,0.0000957784],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.08856413,0.0274109,0.04427505,0.1199262,0.001153842,0.0008050203,0.02228273,0.001892036,0.6936901],"genre_scores_gemma":[0.7762397,0.02444113,0.1103373,0.007034838,0.0005403283,0.0007468772,0.01157308,0.0006168201,0.06846993],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9789806,"threshold_uncertainty_score":0.8695908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05377862158141605,"score_gpt":0.3343231182009377,"score_spread":0.2805444966195216,"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."}}