{"id":"W6887622318","doi":"10.17605/osf.io/5va74","title":"Hospital Library Benchmarking Survey 2017","year":2019,"lang":"en","type":"article","venue":"OSF Preprints (OSF Preprints)","topic":"Health Sciences Research and Education","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Benchmarking; Interlibrary loan; Scope (computer science); Documentation; Information system; MEDLINE","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":[],"consensus_categories":[],"category_scores_codex":[0.01198478,0.000545529,0.0008144718,0.009592051,0.0007171155,0.002383519,0.001574519,0.00063402,0.02879838],"category_scores_gemma":[0.03623144,0.0004798824,0.0007499533,0.02011628,0.0003134245,0.00222636,0.002752939,0.001137024,0.02106518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005596261,"about_ca_system_score_gemma":0.007179846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02342002,"about_ca_topic_score_gemma":0.0203684,"domain_scores_codex":[0.9842445,0.003996675,0.004035467,0.001122504,0.005200377,0.001400397],"domain_scores_gemma":[0.9422245,0.00903176,0.01305892,0.002128634,0.0301626,0.003393614],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0004617515,0.0004115458,0.2244155,0.001571596,0.0001267494,0.00006016143,0.0007055449,0.0004993624,0.0002050055,0.001965904,0.6971,0.07247678],"study_design_scores_gemma":[0.0001542731,0.0002086563,0.5789064,0.0005876861,0.00004631722,0.0001080685,0.001485616,0.0006025269,0.0006681716,0.0003869515,0.4167837,0.0000616159],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.06496904,0.001566194,0.002438794,0.003925339,0.0002883711,0.002411519,0.8691183,0.001210153,0.05407231],"genre_scores_gemma":[0.1558178,0.002833263,0.005157509,0.003660643,0.0004937086,0.0121216,0.7788503,0.0007019224,0.04036334],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02879838,"threshold_uncertainty_score":0.09634018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06531606509460494,"score_gpt":0.3993305799877512,"score_spread":0.3340145148931463,"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."}}