{"id":"W2808481006","doi":"10.21083/partnership.v13i1.4115","title":"Developing Research Data Management Services and Support for Researchers: A Mixed Methods Study","year":2018,"lang":"en","type":"article","venue":"Partnership The Canadian Journal of Library and Information Practice and Research","topic":"Research Data Management Practices","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Council of University Libraries; University of Toronto","funders":"","keywords":"Focus group; Data management; Agency (philosophy); Knowledge management; Research data; Computer science; Data collection; Data science; Medical education; Medicine; Data curation; Business; Database; Sociology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.06569495,0.0001157782,0.0001605759,0.00157391,0.002257558,0.01679876,0.003534115,0.0000640604,0.00001261827],"category_scores_gemma":[0.003998349,0.00007998863,0.00001521908,0.001533071,0.0007190036,0.2358,0.003018254,0.0009366265,0.000008427959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004096652,"about_ca_system_score_gemma":0.001498011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005038588,"about_ca_topic_score_gemma":0.0005821345,"domain_scores_codex":[0.9927068,0.004484731,0.0005234576,0.0003149492,0.00122065,0.000749376],"domain_scores_gemma":[0.9908023,0.006189162,0.0002713159,0.001044866,0.0009806131,0.0007117515],"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":[0.0003537388,0.00004167617,0.0006477583,0.0004763736,0.0002851066,0.0000686576,0.01131069,7.317676e-7,0.000002499741,0.8378563,0.01330351,0.135653],"study_design_scores_gemma":[0.0005581469,0.0009583752,0.003215788,0.0000761863,0.0000203527,0.0001260363,0.0539046,0.001835229,0.0000513652,0.004293919,0.934855,0.000105019],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02281787,0.004706975,0.1009332,0.7312127,0.000785696,0.008056685,0.0000774262,0.00007277799,0.1313366],"genre_scores_gemma":[0.5672271,0.02028055,0.3986457,0.006513203,0.0008893855,0.0002018048,0.0001036635,0.0000487648,0.006089801],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.9215515,"threshold_uncertainty_score":0.9990414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5032391871526627,"score_gpt":0.5427052831848537,"score_spread":0.03946609603219098,"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."}}