{"id":"W6950154734","doi":"10.5281/zenodo.3387548","title":"D2.1: Draft Stakeholder Map & D2.7: Final Stakeholder Map","year":2017,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Research Data Management Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Advanced Scientific Computing Research; Syddansk Universitet; Teknologian Tutkimuskeskus VTT; International Livestock Research Institute; International Business Machines Corporation; European Commission; Institute for Information and Communications Technology Promotion; Institut Teknologi Bandung; Polar Knowledge Canada","keywords":"Deliverable; Scope (computer science); Stakeholder; Stakeholder analysis; Field (mathematics); Stakeholder engagement","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":["metaepi_narrow","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["scholarly_communication","open_science","insufficient_payload"],"category_scores_codex":[0.002744973,0.0002853539,0.0002376043,0.0004153821,0.006464047,0.03357025,0.01201219,0.00008920236,0.005813469],"category_scores_gemma":[0.002204712,0.0002934964,0.00007898698,0.0003976167,0.0003299957,0.02282451,0.01186367,0.0006416459,0.02322015],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001888562,"about_ca_system_score_gemma":0.00001807189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008743964,"about_ca_topic_score_gemma":0.000005119784,"domain_scores_codex":[0.9954343,0.0006634939,0.0004061891,0.001152098,0.001385325,0.0009585695],"domain_scores_gemma":[0.9941581,0.00007666345,0.0003942084,0.004212746,0.0007512933,0.0004069488],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007531053,0.0003687149,0.00003902982,0.0001967767,0.0001362887,0.0001745258,0.0007990833,0.00005305663,0.001910277,0.1338664,0.7703602,0.09202041],"study_design_scores_gemma":[0.0007117434,0.0001545358,0.002400099,0.00004305154,0.00001269807,0.00004463414,0.00009923002,0.0005561676,0.0001957306,0.0006465623,0.9948027,0.0003328216],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01306076,0.0003107678,0.5683727,0.04256697,0.00123145,0.002256182,0.0004893788,0.003227898,0.3684839],"genre_scores_gemma":[0.7307559,0.001071699,0.03411172,0.001829595,0.001451876,0.000001262675,0.003662902,0.004556946,0.2225581],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7176952,"threshold_uncertainty_score":0.9999517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2815112957295474,"score_gpt":0.331258198362191,"score_spread":0.04974690263264359,"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."}}