{"id":"W6950318524","doi":"10.5281/zenodo.7525911","title":"Modernizing Dissemination: Migrating from Nesstar at Statistics Canada's Data Liberation Initiative","year":2022,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Census and Population Estimation","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada","funders":"","keywords":"Metadata; General partnership; Mandate; Modernization theory; Official statistics; Commit; Descriptive statistics","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.04083018,0.000838676,0.0006542503,0.005563764,0.008227992,0.02263694,0.005753737,0.003663188,0.02312653],"category_scores_gemma":[0.07932926,0.0009643605,0.0008737368,0.01234642,0.007910853,0.01682006,0.01166471,0.006192142,0.007109696],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0826915,"about_ca_system_score_gemma":0.3026856,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.944191,"about_ca_topic_score_gemma":0.940282,"domain_scores_codex":[0.9648349,0.005115649,0.001563828,0.002509021,0.01958144,0.006395202],"domain_scores_gemma":[0.8480058,0.01658861,0.002782153,0.01916673,0.07960521,0.0338515],"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":[0.0001497017,0.0001814707,0.01296788,0.0002210208,0.00004185476,0.0003058405,0.004310584,0.001632709,0.001866169,0.09041007,0.691915,0.1959977],"study_design_scores_gemma":[0.00003432481,0.00002615549,0.004983726,0.0001639355,0.0000117594,0.0000561009,0.002065249,0.001242752,0.0007459864,0.006383091,0.9842027,0.00008407402],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.03622744,0.006487951,0.06280747,0.7122082,0.005058211,0.0008659239,0.01099613,0.01901132,0.1463374],"genre_scores_gemma":[0.3105798,0.01996396,0.2982758,0.12507,0.005206598,0.0007147355,0.03838739,0.01485371,0.1869479],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.977363,"threshold_uncertainty_score":0.5999717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1236044118526888,"score_gpt":0.3122263366580421,"score_spread":0.1886219248053533,"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."}}