{"id":"W1584143444","doi":"10.18438/b83g75","title":"Business Intelligence Infrastructure for Academic Libraries","year":2013,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; World Wide Web; Interlibrary loan; Database","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005282812,0.001230204,0.001034156,0.005853633,0.002289525,0.01548468,0.004740016,0.002513594,0.05858376],"category_scores_gemma":[0.01258949,0.0009103783,0.0009957706,0.01281688,0.001057029,0.01509229,0.0112305,0.003293438,0.1074259],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003909873,"about_ca_system_score_gemma":0.00805118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006663974,"about_ca_topic_score_gemma":0.003407865,"domain_scores_codex":[0.9944458,0.001237758,0.0007199167,0.000851611,0.001914497,0.0008303007],"domain_scores_gemma":[0.9899014,0.0009066193,0.0006970523,0.004288888,0.002690505,0.001515412],"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":[0.0001909712,0.0002499402,0.001992647,0.000632292,0.00008246539,0.0003421739,0.0005364522,0.002284404,0.001922212,0.1969081,0.4579948,0.3368635],"study_design_scores_gemma":[0.00002312657,0.00001870209,0.0005869399,0.0001550374,0.00001417064,0.0001388379,0.0002200227,0.005395093,0.001053714,0.03072128,0.9616483,0.00002483195],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.006655905,0.006118737,0.2376391,0.02139029,0.001377447,0.001221612,0.01958314,0.1295529,0.5764609],"genre_scores_gemma":[0.1534674,0.01458106,0.3527722,0.008390381,0.002438559,0.001656477,0.1806891,0.01184799,0.2741567],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05858376,"threshold_uncertainty_score":0.1959822,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03481564118574194,"score_gpt":0.2734112177454564,"score_spread":0.2385955765597145,"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."}}