{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.009698785,0.0005680635,0.000490597,0.002318922,0.001752182,0.00818453,0.002653722,0.001337844,0.01131524],"category_scores_gemma":[0.03468376,0.000724582,0.001568037,0.003836339,0.002257567,0.005801823,0.005877741,0.002803648,0.002211536],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01213194,"about_ca_system_score_gemma":0.008658499,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07200988,"about_ca_topic_score_gemma":0.03814759,"domain_scores_codex":[0.98047,0.007646816,0.00135926,0.002895017,0.006307649,0.001321406],"domain_scores_gemma":[0.966023,0.01353077,0.002133627,0.01017709,0.006919466,0.001215967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0005324974,0.0005418257,0.01317356,0.0003497935,0.00009083531,0.0005868744,0.002561073,0.2136726,0.002576142,0.5731333,0.01799533,0.1747862],"study_design_scores_gemma":[0.00005886968,0.0001036195,0.00280305,0.0001672854,0.00003414034,0.0004192617,0.000834566,0.6400064,0.003183567,0.2573141,0.0950165,0.00005865287],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09209898,0.0007263612,0.820099,0.007310668,0.0001807846,0.001938737,0.005732058,0.008032702,0.06388064],"genre_scores_gemma":[0.4962793,0.0006092259,0.4714074,0.0008337462,0.00008313229,0.001084135,0.006625853,0.000864418,0.02221289],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9918154,"threshold_uncertainty_score":0.1431815,"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."}}