{"id":"W4396736647","doi":"10.1038/s41597-024-03280-6","title":"Getting your DUCs in a row - standardising the representation of Digital Use Conditions","year":2024,"lang":"en","type":"article","venue":"Scientific Data","topic":"Research Data Management Practices","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; Ontario Brain Institute","funders":"Institut National de la Santé et de la Recherche Médicale; European Commission","keywords":"Computer science; Context (archaeology); Ambiguity; Asset (computer security); Data science; Granularity; Representation (politics); Task (project management); Diversity (politics); Knowledge management; Risk analysis (engineering); Business; Systems engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03025257,0.001224074,0.001296185,0.008497762,0.003729067,0.02392035,0.003074095,0.004479668,0.005912913],"category_scores_gemma":[0.07247039,0.001244668,0.001632039,0.00635436,0.01477183,0.03870075,0.01250688,0.007705025,0.003001986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004770067,"about_ca_system_score_gemma":0.007699737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006302468,"about_ca_topic_score_gemma":0.006261345,"domain_scores_codex":[0.9732006,0.01215037,0.005274548,0.002927305,0.005188927,0.001258156],"domain_scores_gemma":[0.9291704,0.02329508,0.004584493,0.02861262,0.01115631,0.003181073],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009008485,0.00006953826,0.003481986,0.0003501637,0.00003623175,0.0003952517,0.00776178,0.002514232,0.00182256,0.8716067,0.01295265,0.09891888],"study_design_scores_gemma":[0.00002207827,0.00007316565,0.001470853,0.001408483,0.00005489788,0.000945224,0.009730507,0.009769272,0.004603938,0.5316194,0.4401254,0.0001767155],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0205255,0.001541458,0.8708756,0.02338485,0.001134113,0.0008013211,0.002525597,0.003380274,0.07583134],"genre_scores_gemma":[0.2371848,0.002142118,0.7413954,0.00266714,0.0004508345,0.001021606,0.003114146,0.001277426,0.01074662],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9697474,"threshold_uncertainty_score":0.1599928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3149498459064001,"score_gpt":0.4554718182854468,"score_spread":0.1405219723790466,"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."}}