{"id":"W3209571917","doi":"10.5281/zenodo.4570030","title":"Institutional Research Data Management Services Capacity Survey INSIGHTS Report #2 Current Capacity within Institutions: Highly Qualified Personnel, and Infrastructure and Services","year":2021,"lang":"en","type":"report","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Research Data Management Practices","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; University of Toronto; University of Victoria; York University; University of Guelph; Queen's University","funders":"","keywords":"Business; Capacity management; Survey data collection; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.01630137,0.0005825076,0.0004073859,0.006465477,0.00123585,0.006021395,0.0008961065,0.0009861534,0.03293867],"category_scores_gemma":[0.04661743,0.0004803274,0.0004327559,0.01667809,0.0004810931,0.003909118,0.003390942,0.001418883,0.02244779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006007785,"about_ca_system_score_gemma":0.01736796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03968078,"about_ca_topic_score_gemma":0.03816955,"domain_scores_codex":[0.9756099,0.004567975,0.002103582,0.001031818,0.01308199,0.003604775],"domain_scores_gemma":[0.9270324,0.01508057,0.008927255,0.003945004,0.03752895,0.00748572],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001574988,0.0002053136,0.08227575,0.001022318,0.00004113098,0.00008054746,0.002106525,0.0005866396,0.0009038433,0.005901907,0.8037252,0.1029933],"study_design_scores_gemma":[0.00001759566,0.0001189125,0.1477791,0.0004044603,0.00002151478,0.0000889838,0.007572328,0.0003170191,0.001429332,0.0005826828,0.8416114,0.00005662037],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.08412234,0.001864789,0.007523404,0.02172268,0.000571381,0.002284285,0.6733102,0.002589996,0.206011],"genre_scores_gemma":[0.2664447,0.005390795,0.01464535,0.005626583,0.0006089043,0.006199279,0.5242233,0.001108365,0.1757527],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9991039,"threshold_uncertainty_score":0.1101909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3223392772057505,"score_gpt":0.377606394244221,"score_spread":0.05526711703847054,"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."}}