{"id":"W4287901858","doi":"10.5281/zenodo.3611327","title":"CESSDA ERIC Persistent Identifier Policy 2019","year":2020,"lang":"en","type":"report","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Identifier; Genealogy; Computer science; History; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.007048517,0.0003406931,0.0005480784,0.001058266,0.002264203,0.005633607,0.005541214,0.0001923637,0.04562254],"category_scores_gemma":[0.01667399,0.0003152094,0.0003751046,0.00235273,0.0002873099,0.0006037191,0.007852444,0.0006590731,0.1068314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006269115,"about_ca_system_score_gemma":0.00007622045,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002629475,"about_ca_topic_score_gemma":0.000002253561,"domain_scores_codex":[0.9910113,0.001117437,0.001077258,0.001399704,0.004788586,0.0006057502],"domain_scores_gemma":[0.9941674,0.0001196987,0.0007092378,0.001868665,0.002668978,0.0004659843],"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":[0.00002328441,0.00007735231,6.280471e-7,0.0001066087,0.0001161139,0.00002762555,0.0005746024,0.00001902559,0.00004391498,0.002003307,0.882122,0.1148856],"study_design_scores_gemma":[0.00022878,0.0001573546,0.0002729614,0.00005763394,0.00005777888,0.00008636826,0.0009149892,0.00006834587,0.00001297174,0.0008391467,0.9969706,0.0003330504],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0001567333,0.0004071135,0.003336065,0.009062422,0.001192547,0.0008773439,0.003311401,0.000802867,0.9808535],"genre_scores_gemma":[0.1127066,0.00858233,0.0008749174,0.004617834,0.007742745,4.694113e-7,0.05657834,0.01069642,0.7982003],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1826532,"threshold_uncertainty_score":0.99993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.291310094241864,"score_gpt":0.3978849953402161,"score_spread":0.1065749010983521,"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."}}