{"id":"W2094439764","doi":"10.6017/ital.v34i1.5664","title":"Linked Data in Libraries: A Case Study of Harvesting and Sharing Bibliographic Metadata with BIBFRAME","year":2015,"lang":"en","type":"article","venue":"Information Technology and Libraries","topic":"Library Science and Information Systems","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Metadata; Computer science; World Wide Web; Linked data; Digital library; Meta Data Services; Information retrieval; Data sharing; Metadata repository; Semantic Web","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0005591505,0.0001255388,0.0002229914,0.004754177,0.0001387914,0.001573274,0.001248825,0.0001120304,0.000001026966],"category_scores_gemma":[0.0001313571,0.00009554771,0.000005920707,0.007378663,0.0002984787,0.1129793,0.001854867,0.0001815397,0.000001713844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002322718,"about_ca_system_score_gemma":0.0001223369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002446218,"about_ca_topic_score_gemma":0.00002998629,"domain_scores_codex":[0.9988077,0.00002851295,0.0005622506,0.0002156363,0.0002106545,0.0001752356],"domain_scores_gemma":[0.9986156,0.00007386271,0.0002951313,0.00087799,0.00005963511,0.00007776301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.00003403755,0.0000805421,0.6384359,0.0001329724,0.00005206847,0.0001016545,0.05795627,0.00006634272,0.000002567242,0.2737869,0.0003853208,0.02896543],"study_design_scores_gemma":[0.00856454,0.003294733,0.03194007,0.0004450089,0.0000326252,0.007295558,0.5630517,0.3049232,0.0005569002,0.04690024,0.03161292,0.001382504],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9641573,0.0003111996,0.03341183,0.0007381581,0.00005858386,0.000369398,0.00001136601,0.0002894213,0.0006527053],"genre_scores_gemma":[0.9849739,0.00002093207,0.01477993,0.0001643797,0.00000563696,0.0000172005,0.00001756923,0.000002740375,0.00001768425],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6064959,"threshold_uncertainty_score":0.9994632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0631738486104441,"score_gpt":0.2555790721002711,"score_spread":0.192405223489827,"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."}}