{"id":"W7095856872","doi":"","title":"Library of Congress Cataloging-in-Publication Data:","year":2014,"lang":"en","type":"article","venue":"","topic":"Library Science and Information Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Section (typography); Authorization; Permission; National library; Government (linguistics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0007777732,0.001992546,0.003078238,0.006262717,0.004055062,0.01390541,0.002442429,0.001854231,0.8884344],"category_scores_gemma":[0.005793989,0.0007606311,0.0007153034,0.02054009,0.001836691,0.003759426,0.001480584,0.002104431,0.8831199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009577484,"about_ca_system_score_gemma":0.03962715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4832419,"about_ca_topic_score_gemma":0.5402814,"domain_scores_codex":[0.9990875,0.00002911933,0.00004374715,0.000135531,0.0005564679,0.0001477337],"domain_scores_gemma":[0.9918407,0.0002620609,0.0001278022,0.0005321188,0.005963821,0.001273369],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001501083,0.0000178028,0.00009676663,0.0001829246,0.000003636136,0.00001552175,0.00002256274,0.00003814934,0.0001059115,0.0007809375,0.9792962,0.01942465],"study_design_scores_gemma":[0.00001240804,0.00000614069,0.0004823774,0.0001667101,0.000006047881,0.00001690773,0.0000580665,0.0000387231,0.00006665241,0.0002027495,0.9989313,0.00001178075],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000202983,0.001409586,0.0003735374,0.0009874727,0.001627761,0.0002612156,0.06382717,0.001666978,0.9296433],"genre_scores_gemma":[0.0009333507,0.002165249,0.0004219218,0.0003490813,0.0001577408,0.00006725821,0.02083513,0.0005658224,0.9745045],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4832419,"threshold_uncertainty_score":0.9608583,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02931987954703897,"score_gpt":0.2386234215370888,"score_spread":0.2093035419900498,"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."}}