{"id":"W2240516920","doi":"","title":"Data Management for Graduate Students: A case study at Oregon State University","year":2015,"lang":"en","type":"article","venue":"Practical academic librarianship","topic":"Research Data Management Practices","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Graduate students; Quarter (Canadian coin); Value (mathematics); State (computer science); Academic library; Position (finance); Data management; Computer science; Library science; Medical education; Mathematics education; Psychology; Medicine; Business; Geography; Data mining","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","open_science"],"consensus_categories":["scholarly_communication","open_science"],"category_scores_codex":[0.007399692,0.0002754275,0.0002726894,0.0002923299,0.0003446941,0.002184234,0.008715918,0.0001020139,0.000009154871],"category_scores_gemma":[0.0024444,0.000260416,0.00004291837,0.0009465409,0.0001039627,0.08214826,0.02046853,0.0009543602,0.0001614596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002341907,"about_ca_system_score_gemma":0.0002059666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001281079,"about_ca_topic_score_gemma":0.00003990569,"domain_scores_codex":[0.9943542,0.001239193,0.0004412027,0.001563243,0.001639313,0.0007628659],"domain_scores_gemma":[0.9939083,0.001889611,0.0003106821,0.003062043,0.0001155839,0.0007138036],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0022041,0.003535599,0.03878031,0.0003181359,0.001773902,0.0721833,0.003929208,0.00005018571,0.000008170565,0.5421841,0.3073362,0.02769684],"study_design_scores_gemma":[0.00810637,0.001038677,0.003881888,0.00004528978,0.0004413716,0.001533795,0.01676969,0.02158113,0.00003025236,0.01321838,0.9323497,0.001003419],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1423023,0.0001004557,0.803589,0.04103458,0.0007050753,0.005426743,0.0002949536,0.0007018931,0.005844927],"genre_scores_gemma":[0.7930104,0.000962543,0.1755888,0.001999079,0.0003834177,0.0001418373,0.0003106185,0.00009953959,0.0275037],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6507081,"threshold_uncertainty_score":0.9999848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.606775529061156,"score_gpt":0.4720976306517437,"score_spread":0.1346778984094122,"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."}}