{"id":"W4280609400","doi":"10.1080/19386389.2022.2051979","title":"Numismatics & Bibliographic Description: How Rutgers University Libraries Described Coins with MODS","year":2022,"lang":"en","type":"article","venue":"Journal of Library Metadata","topic":"Digital and Traditional Archives Management","field":"Arts and Humanities","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Metadata; Computer science; World Wide Web; Metadata repository; Interoperability; Resource Description and Access; Realia; Special collections; Cataloging; Meta Data Services; Controlled vocabulary; Library science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.009470806,0.0003807309,0.0003898732,0.009301331,0.009870493,0.02684453,0.002433743,0.00185863,0.01145933],"category_scores_gemma":[0.02968041,0.0006493939,0.0004919218,0.01467017,0.01445146,0.02884473,0.01091459,0.002719121,0.003386352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01713773,"about_ca_system_score_gemma":0.01365018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08540837,"about_ca_topic_score_gemma":0.1482271,"domain_scores_codex":[0.9828007,0.0104354,0.001035657,0.000919686,0.004148696,0.0006598032],"domain_scores_gemma":[0.9887775,0.004629703,0.001249824,0.002546802,0.002220457,0.0005757642],"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":[0.0000416491,0.00004199498,0.006614391,0.0002524766,0.0000197044,0.0007288959,0.1759426,0.000574302,0.0007093134,0.6081551,0.07033826,0.1365813],"study_design_scores_gemma":[0.000005622704,0.00001215621,0.002337357,0.0004489283,0.00001600982,0.0005643149,0.07912062,0.0008137621,0.000807352,0.0303787,0.8854125,0.00008271119],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.08884563,0.004770917,0.07873888,0.07281005,0.001597958,0.0003299772,0.001251483,0.002695258,0.7489598],"genre_scores_gemma":[0.7309438,0.004566323,0.06856005,0.007094549,0.0003660188,0.0002315176,0.001140738,0.002259416,0.1848375],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9731555,"threshold_uncertainty_score":0.1698225,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06207260552185907,"score_gpt":0.1738001835908003,"score_spread":0.1117275780689412,"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."}}