{"id":"W3113007096","doi":"10.23889/ijpds.v5i5.1543","title":"Transformation of Data Access Models In BC","year":2020,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Scientific Research and Technology","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Timeline; Provisioning; Computer science; Data access; Data management; Database; Data science; Operating system; Statistics","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":["scholarly_communication","open_science"],"consensus_categories":[],"category_scores_codex":[0.001994894,0.00005820205,0.00009303653,0.0004971209,0.0001136851,0.0006508269,0.01778642,0.00002665822,0.00001053254],"category_scores_gemma":[0.000704658,0.00005160803,0.00001827214,0.001029387,0.0001148059,0.02429256,0.00212244,0.0001345283,0.000003284688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004983069,"about_ca_system_score_gemma":0.0002540646,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001378738,"about_ca_topic_score_gemma":0.00006242539,"domain_scores_codex":[0.9977813,0.00002339826,0.0004407956,0.0004431724,0.001111489,0.0001998182],"domain_scores_gemma":[0.9984396,0.00006051931,0.0001996519,0.0007832141,0.0004067876,0.0001102563],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001129416,0.0001520306,0.007091348,0.00002735757,0.00002896503,0.00001745019,0.001000511,0.01578167,0.004030248,0.4106592,0.004746005,0.5563523],"study_design_scores_gemma":[0.0003268544,0.00002464419,0.003409724,0.00001439166,8.572271e-7,0.00001663395,0.00002374903,0.9692429,0.0005276172,0.0240651,0.002292457,0.00005506803],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02116979,0.00002233739,0.9665974,0.01075156,0.000807372,0.0001677417,0.0002266186,0.00002547966,0.0002317239],"genre_scores_gemma":[0.9603515,0.00003926222,0.0391455,0.0001471633,0.0000654314,0.000002132588,0.0002405236,0.000002371756,0.000006142356],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9534612,"threshold_uncertainty_score":0.9893541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3386497578390779,"score_gpt":0.4705729874426805,"score_spread":0.1319232296036026,"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."}}