{"id":"W6969249269","doi":"10.5281/zenodo.5750160","title":"Making metadata FAIR: Combining DDI solutions with other standards in official statistics","year":2021,"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":"Statistics Canada","funders":"","keywords":"Metadata; Database catalog; Metadata repository; Data element; Meta Data Services; Geospatial metadata; Data dictionary","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.1600688,0.0008596416,0.001533302,0.01536629,0.005396788,0.03331248,0.008249694,0.004210321,0.007367157],"category_scores_gemma":[0.1658296,0.001600166,0.001987263,0.01978512,0.00988117,0.06057192,0.03255935,0.008190621,0.004453571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01610619,"about_ca_system_score_gemma":0.0241994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02164663,"about_ca_topic_score_gemma":0.01115037,"domain_scores_codex":[0.9113445,0.03051445,0.01487517,0.006773033,0.03313468,0.003358186],"domain_scores_gemma":[0.8084465,0.058125,0.006892639,0.08338887,0.03584752,0.007299555],"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":[0.0001255243,0.0001840789,0.004184957,0.0005207183,0.00006373214,0.0002174478,0.008083808,0.002198262,0.001423932,0.6137847,0.03560214,0.3336107],"study_design_scores_gemma":[0.00006951548,0.00005409773,0.001012649,0.001000272,0.00005722224,0.0002511083,0.004002023,0.01113936,0.004625684,0.4208348,0.556783,0.0001702364],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006265216,0.00248788,0.8984511,0.03341002,0.001261851,0.0005531631,0.001543293,0.01379741,0.04223008],"genre_scores_gemma":[0.06549887,0.003261068,0.9041243,0.00324047,0.0008640218,0.0007474406,0.006056388,0.00582609,0.01038135],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9917503,"threshold_uncertainty_score":0.8465349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1439828438117428,"score_gpt":0.3391352643790387,"score_spread":0.1951524205672959,"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."}}