{"id":"W6949975376","doi":"10.5281/zenodo.2555323","title":"Dataverse for the Canadian Research Community: Developing reusable and scalable tools for data deposit, curation, and sharing","year":2019,"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":"University of Toronto; Queen's University","funders":"","keywords":"Summit; Scalability; Presentation (obstetrics); Data sharing; Key (lock); Data collection; Context (archaeology)","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":[0.0554761,0.002761326,0.002368808,0.013357,0.008476586,0.01873002,0.009282662,0.005023954,0.1274048],"category_scores_gemma":[0.1155763,0.003034795,0.002910414,0.02353927,0.003963213,0.02175232,0.02474183,0.009011631,0.07993142],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01186201,"about_ca_system_score_gemma":0.08795151,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4042885,"about_ca_topic_score_gemma":0.5627353,"domain_scores_codex":[0.9778345,0.004147404,0.002028839,0.002047743,0.0120991,0.001842502],"domain_scores_gemma":[0.8786681,0.02807243,0.003089834,0.03152605,0.04239457,0.01624907],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009271893,0.00002275953,0.0004059851,0.0005829447,0.00005762109,0.00006913534,0.0007323911,0.0001556031,0.0008818342,0.01192535,0.9418877,0.04318588],"study_design_scores_gemma":[0.00005764254,0.00001080769,0.0006755353,0.0004716439,0.00003667062,0.00003956692,0.0004659707,0.0006745194,0.001131768,0.01268881,0.9836507,0.00009628107],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"methods","genre_scores_codex":[0.001752048,0.005352172,0.2239617,0.09045378,0.00889424,0.002681361,0.376902,0.1781624,0.1118404],"genre_scores_gemma":[0.01062475,0.007857125,0.4907719,0.01266919,0.001643193,0.003480284,0.3356622,0.05284563,0.08444576],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9907174,"threshold_uncertainty_score":0.8038706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6375805133337603,"score_gpt":0.459173414199544,"score_spread":0.1784070991342163,"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."}}