{"id":"W3116320491","doi":"10.2218/ijdc.v15i1.708","title":"Access Some Areas: Reforming Access Categories for Data in a Social Science Data Archive","year":2020,"lang":"en","type":"article","venue":"International Journal of Digital Curation","topic":"Research Data Management Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Data access; Data science; Computer science; World Wide Web; Database","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":[0.08382276,0.0005042372,0.001375238,0.01243962,0.009239274,0.01899681,0.004433256,0.002658391,0.005871659],"category_scores_gemma":[0.1440709,0.001050004,0.001823781,0.009805987,0.01514929,0.03257061,0.01560685,0.007199634,0.001707959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009293781,"about_ca_system_score_gemma":0.01736405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03013497,"about_ca_topic_score_gemma":0.02146662,"domain_scores_codex":[0.925289,0.03534051,0.01434014,0.007448556,0.01407301,0.003508773],"domain_scores_gemma":[0.7883074,0.07939839,0.007837107,0.07251128,0.04559471,0.00635107],"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":[0.0001764392,0.0001016855,0.007224151,0.0004330495,0.00004490349,0.0002519082,0.02376173,0.001727119,0.002503358,0.8441275,0.01536932,0.1042788],"study_design_scores_gemma":[0.00006625122,0.0001499844,0.006122552,0.001087129,0.00008113671,0.0004596213,0.0221339,0.008014148,0.005864087,0.3535743,0.6021835,0.0002633778],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07841291,0.0009083819,0.8433105,0.02135747,0.0008850456,0.002244789,0.004228939,0.004701475,0.04395051],"genre_scores_gemma":[0.2490012,0.0005585157,0.7285246,0.003593578,0.0003749797,0.002250212,0.004953106,0.001809181,0.008934597],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9810032,"threshold_uncertainty_score":0.4433025,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3445338487751635,"score_gpt":0.4845747686055644,"score_spread":0.140040919830401,"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."}}