{"id":"W6911269502","doi":"10.5281/zenodo.10463205","title":"World Data System Town Hall for Scientific Data Repositories","year":2024,"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":"Ocean Networks Canada Society","funders":"U.S. Department of Energy","keywords":"Town hall; Real world data; World class; Big data; World wide","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":["sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["scholarly_communication","open_science"],"category_scores_codex":[0.006235794,0.0001623153,0.0001566706,0.0006315476,0.003098449,0.06583723,0.02131312,0.00002821295,0.0002278013],"category_scores_gemma":[0.002328274,0.0001576745,0.00003077666,0.002268881,0.0002697379,0.03389475,0.03240261,0.0002828765,0.002052001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001785411,"about_ca_system_score_gemma":0.00002521329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004430776,"about_ca_topic_score_gemma":0.000008229707,"domain_scores_codex":[0.9958926,0.0004105565,0.0003534507,0.001844542,0.0009411793,0.00055764],"domain_scores_gemma":[0.9918495,0.000199453,0.0001225539,0.007099879,0.0005240879,0.0002044599],"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":[0.00001766632,0.00004590737,6.758599e-7,0.0003330653,0.00007062442,0.00005601939,0.0001631769,0.000007734265,0.0004123773,0.3074437,0.6279568,0.06349228],"study_design_scores_gemma":[0.0001307103,0.0000762906,0.00002005903,0.00009613121,0.00002033995,0.0000661315,0.0001766522,0.06723489,0.0001119652,0.0001258277,0.9317784,0.0001626236],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0001972322,0.0006832791,0.894974,0.007200281,0.001925855,0.001359916,0.003651382,0.003834241,0.08617385],"genre_scores_gemma":[0.5110625,0.0007002339,0.1147677,0.0003764626,0.003814379,0.000001605066,0.1419719,0.005569999,0.2217353],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7802063,"threshold_uncertainty_score":0.998725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.227460249325985,"score_gpt":0.3475939176037501,"score_spread":0.1201336682777651,"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."}}