{"id":"W2907069234","doi":"10.14288/1.0372048","title":"Research Data Management Training Landscape in Canada : A White Paper","year":2018,"lang":"en","type":"report","venue":"cIRcle (University of British Columbia)","topic":"Research Data Management Practices","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Université de Montréal; University of Alberta; University of Toronto; Carleton University","funders":"Université de Montréal; Queen's University; University of Toronto; McMaster University","keywords":"White (mutation); Training (meteorology); White paper; Geography; Environmental resource management; Archaeology; Environmental science; Meteorology; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.03007592,0.0004790058,0.0005214436,0.005568258,0.01971407,0.02000099,0.004211602,0.002869608,0.01251131],"category_scores_gemma":[0.03963801,0.000981927,0.0005773263,0.02000766,0.005996312,0.003962165,0.005947919,0.004975372,0.001743739],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.2045873,"about_ca_system_score_gemma":0.5250869,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9892443,"about_ca_topic_score_gemma":0.9930835,"domain_scores_codex":[0.9582784,0.003167063,0.001645687,0.003050931,0.02404219,0.00981574],"domain_scores_gemma":[0.8797699,0.01343413,0.003561077,0.003892898,0.07057482,0.02876715],"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":[0.0001348271,0.000239133,0.01825092,0.0006005235,0.00004428826,0.001087264,0.01311657,0.001682347,0.001375483,0.1309297,0.6074643,0.2250746],"study_design_scores_gemma":[0.00001081168,0.00002656809,0.02304585,0.0004918264,0.00001498355,0.00009678322,0.01091445,0.0005469454,0.0006063529,0.002251841,0.9619321,0.0000615219],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.06777226,0.01070947,0.005841292,0.4440995,0.002116344,0.0006258719,0.01252902,0.001214142,0.4550922],"genre_scores_gemma":[0.4553558,0.0217636,0.02042299,0.06857441,0.000650423,0.0004022992,0.01338329,0.0009786743,0.4184685],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9957884,"threshold_uncertainty_score":0.922566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1466912211341474,"score_gpt":0.3098245144573988,"score_spread":0.1631332933232514,"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."}}