{"id":"W6912184218","doi":"10.5281/zenodo.2559256","title":"Tri-Agency Research Data Management Policy Development","year":2019,"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":"Natural Sciences and Engineering Research Council","funders":"","keywords":"Data management; Presentation (obstetrics); Research data; Policy development; Data collection; Public policy; Management development","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":[0.1480659,0.001468576,0.001553464,0.005911747,0.008063776,0.02665217,0.01085096,0.03593494,0.1107083],"category_scores_gemma":[0.1418581,0.002504343,0.002827369,0.01053483,0.003616276,0.01894058,0.01147066,0.02218098,0.061641],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02932189,"about_ca_system_score_gemma":0.181924,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1099683,"about_ca_topic_score_gemma":0.09330358,"domain_scores_codex":[0.8794473,0.02254756,0.007082722,0.006342944,0.07454447,0.01003499],"domain_scores_gemma":[0.821918,0.03145253,0.007995665,0.01981612,0.09929209,0.01952559],"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":[0.00004595334,0.0001007876,0.0001957402,0.0001421344,0.00001113168,0.00006286806,0.0002220732,0.0001902341,0.0002819651,0.05074452,0.9348629,0.01313973],"study_design_scores_gemma":[0.0000283682,0.00001681976,0.0001978416,0.000143592,0.000006580321,0.00001862484,0.0001705109,0.0002008541,0.0002556623,0.002545458,0.9963941,0.0000214323],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"methods","genre_scores_codex":[0.00133025,0.003099714,0.02084166,0.5678723,0.01746259,0.003801401,0.01269877,0.003288356,0.3696049],"genre_scores_gemma":[0.01304524,0.004824621,0.06403238,0.224186,0.005305423,0.005484234,0.01693115,0.00193052,0.6642604],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.989149,"threshold_uncertainty_score":0.7830569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1996830023573624,"score_gpt":0.3635941877660667,"score_spread":0.1639111854087043,"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."}}