{"id":"W6948750158","doi":"10.5281/zenodo.1118378","title":"Perspectives on the Implementation of the CESSDA Metadata Model","year":2017,"lang":"en","type":"article","venue":"Figshare","topic":"Research Data Management Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Library and Archives Canada","funders":"","keywords":"Metadata; Usability; Meta Data Services; Metadata repository; Documentation; Metadata modeling; Data element; Geospatial metadata; Service (business)","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","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.08989412,0.0006785897,0.0006254176,0.002773646,0.004028837,0.01849396,0.003156424,0.004871727,0.003633019],"category_scores_gemma":[0.09049212,0.0008051543,0.0008025061,0.003642391,0.006561846,0.01862143,0.009292783,0.005317862,0.0008470793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01292875,"about_ca_system_score_gemma":0.01810599,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01636519,"about_ca_topic_score_gemma":0.01007422,"domain_scores_codex":[0.9047029,0.06670691,0.005546206,0.003297782,0.0159593,0.003786878],"domain_scores_gemma":[0.9062065,0.04190374,0.004185697,0.01613135,0.02817283,0.003399908],"domain_codex":null,"domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000300126,0.000659539,0.02546308,0.001108508,0.0000659634,0.001068248,0.0923146,0.00379575,0.01355653,0.6374027,0.0109477,0.2133172],"study_design_scores_gemma":[0.0001199068,0.0008367541,0.01234895,0.003341805,0.00006915438,0.001034954,0.1539059,0.01356687,0.01561843,0.121541,0.6773351,0.0002811634],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4134399,0.004667461,0.2773908,0.1326229,0.000735872,0.001028117,0.0005559995,0.001157752,0.1684014],"genre_scores_gemma":[0.8081644,0.001930135,0.1702114,0.00573957,0.0001160694,0.000626458,0.0008090695,0.0003290564,0.01207376],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.981506,"threshold_uncertainty_score":0.4754112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3015398920012848,"score_gpt":0.4428655828141539,"score_spread":0.1413256908128691,"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."}}