{"id":"W2912172308","doi":"10.1002/lrh2.10187","title":"Cross‐Network Directory Service: Infrastructure to enable collaborations across distributed research networks","year":2019,"lang":"en","type":"article","venue":"Learning Health Systems","topic":"Research Data Management Practices","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"U.S. Food and Drug Administration; Hamilton Health Sciences Foundation; University of Michigan; U.S. Department of Health and Human Services","keywords":"Directory service; Metadata; Workgroup; Computer science; Directory; World Wide Web; Service (business); Lightweight Directory Access Protocol; Software; Computer network","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01303815,0.0002333626,0.000426006,0.0002045468,0.001909771,0.008053669,0.00285072,0.0001582616,0.00003240011],"category_scores_gemma":[0.0009434405,0.0002270419,0.0000360712,0.006085861,0.00005009112,0.007343908,0.002116405,0.00158196,0.000609052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007208994,"about_ca_system_score_gemma":0.0007606283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002785172,"about_ca_topic_score_gemma":0.000389841,"domain_scores_codex":[0.9918158,0.002851182,0.0006734706,0.001067049,0.001521629,0.002070885],"domain_scores_gemma":[0.9949406,0.001158718,0.0003772108,0.001825733,0.001083978,0.0006137339],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002721353,0.00002261907,0.05111251,0.0004693473,0.00003194418,0.000009771384,0.001004177,0.8999089,0.00001558749,0.01517032,0.03094197,0.001285655],"study_design_scores_gemma":[0.0002848755,0.000262845,0.03035126,0.0002246024,9.774993e-7,0.000005112587,0.0008587574,0.2441698,0.000001405752,0.00002489724,0.7236121,0.0002034183],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1005665,0.004118594,0.8596266,0.01600914,0.006600194,0.007251122,0.0001453776,0.001399825,0.004282665],"genre_scores_gemma":[0.9768047,0.0003893726,0.004217894,0.001206169,0.00117574,0.0003686679,0.0003465913,0.00006414379,0.01542677],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8762382,"threshold_uncertainty_score":0.9993896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09153399660153254,"score_gpt":0.4461655314395463,"score_spread":0.3546315348380138,"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."}}