{"id":"W4318021337","doi":"10.7191/jeslib.624","title":"There's no \"I\" in Research Data Management: Reshaping RDM Services Toward a Collaborative Multi-Stakeholder Model","year":2023,"lang":"en","type":"article","venue":"Journal of eScience Librarianship","topic":"Research Data Management Practices","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"RDM; Knowledge management; Stakeholder; Computer science; Service (business); Data management; World Wide Web; Public relations; Business; Political science; Database","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication","open_science"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0188272,0.0002007504,0.0003019138,0.002244792,0.0003528741,0.00648376,0.0170497,0.00007918877,0.00001512116],"category_scores_gemma":[0.001295154,0.0001667185,0.00004450785,0.009872229,0.0002812408,0.09979646,0.007361723,0.0009934384,0.0001471494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009793516,"about_ca_system_score_gemma":0.000638649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004112075,"about_ca_topic_score_gemma":0.00004812745,"domain_scores_codex":[0.9934841,0.001038316,0.0007716524,0.0009396295,0.002743649,0.00102269],"domain_scores_gemma":[0.9955517,0.0008761137,0.000477718,0.002283923,0.0005170946,0.000293453],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005552832,0.001203183,0.01611488,0.001515979,0.0003173543,0.007996379,0.01649303,0.02723006,0.003057089,0.8451086,0.05804518,0.02236293],"study_design_scores_gemma":[0.001210963,0.0001878621,0.01608309,0.0005656871,0.000009327102,0.00001180482,0.005910119,0.9442731,0.000154265,0.008783587,0.02250551,0.0003046829],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07614661,0.003412705,0.7357811,0.09241442,0.002519945,0.003540437,0.0002175805,0.0005504877,0.08541667],"genre_scores_gemma":[0.5609431,0.004560022,0.4241058,0.001457745,0.0003434056,0.00004916164,0.00003519141,0.00006229959,0.008443249],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.917043,"threshold_uncertainty_score":0.9945476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7485915573649452,"score_gpt":0.489634210264553,"score_spread":0.2589573471003922,"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."}}