{"id":"W1586724124","doi":"","title":"Resource Description and Access: From AACR to RDA","year":2011,"lang":"en","type":"article","venue":"eYLS (Yale Law School)","topic":"Library Science and Information Systems","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Rural Development Administration","keywords":"Resource Description and Access; Computer science; Resource (disambiguation); Set (abstract data type); World Wide Web; Cataloging; Information retrieval; Library science; Computer network; Programming language","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002684401,0.0001120769,0.0001267732,0.00008257206,0.0001840008,0.001082616,0.001302776,0.00005436587,0.0001651603],"category_scores_gemma":[0.00002672357,0.00009612904,0.00002997827,0.0003980022,0.00004428639,0.01125435,0.0005048497,0.0000946368,0.001024764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001983274,"about_ca_system_score_gemma":0.00003627084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001337935,"about_ca_topic_score_gemma":0.00006528471,"domain_scores_codex":[0.9988237,0.00005465855,0.0002744376,0.0003171528,0.0002877611,0.0002422634],"domain_scores_gemma":[0.9989879,0.00002462638,0.00008578584,0.0005536959,0.00004026177,0.0003077641],"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":[0.00008383078,0.0001785218,0.08952054,0.0000619261,0.00006168485,0.00004181952,0.0549772,0.00007673577,0.00461072,0.6095155,0.1975635,0.04330801],"study_design_scores_gemma":[0.0006149376,0.0002450396,0.0952678,0.0001108391,0.000003675425,0.00002083456,0.0009619214,0.003914781,0.009751244,0.0159567,0.8725273,0.0006249141],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7120557,0.0001976713,0.1242574,0.001378501,0.001029178,0.0004430375,0.00001455621,0.0004637068,0.1601603],"genre_scores_gemma":[0.9763067,0.000006152698,0.0146472,0.007770122,0.0001454577,0.00001884565,0.000004951333,0.000006026637,0.001094497],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6749638,"threshold_uncertainty_score":0.9999543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04315769730589279,"score_gpt":0.2375497910245473,"score_spread":0.1943920937186545,"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."}}