{"id":"W2605462390","doi":"10.23889/ijpds.v1i1.357","title":"Balancing Privacy and Utility in Secondary Data Use to Inform Policy","year":2017,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Ethics in Clinical Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"PolicyWise for Children & Families","funders":"","keywords":"Safeguarding; Data sharing; Data governance; General partnership; Information governance; Information privacy; Data access; Data Protection Act 1998; Business; Corporate governance; Repurposing; Data collection; Privacy policy; Information sharing; Data security; Consistency (knowledge bases); Internet privacy; Computer science; Computer security; Information system; Data quality; Political science; Management information systems; Engineering; Marketing; World Wide Web; Law; Sociology","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"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.3011019,0.0005196639,0.001337137,0.004916463,0.01187801,0.04014827,0.006527473,0.0126868,0.009050452],"category_scores_gemma":[0.361612,0.001155349,0.001244328,0.007462833,0.05176066,0.02683343,0.02281007,0.01203501,0.001573696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04190383,"about_ca_system_score_gemma":0.08650831,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05235806,"about_ca_topic_score_gemma":0.03506681,"domain_scores_codex":[0.6658976,0.2701604,0.009984639,0.01067654,0.0308882,0.01239256],"domain_scores_gemma":[0.3726629,0.510132,0.01769786,0.04848536,0.04128943,0.009732502],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001498409,0.00007414769,0.00941117,0.0004946551,0.00007555938,0.0002671147,0.02057864,0.002726568,0.0003299879,0.8983414,0.01933863,0.04821237],"study_design_scores_gemma":[0.00007561245,0.00008872592,0.004461848,0.004314028,0.0000897314,0.0001978111,0.02151905,0.00571034,0.001834622,0.7413033,0.2202823,0.0001225547],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.05478743,0.007588391,0.09198762,0.5558968,0.00129291,0.001044908,0.0008239006,0.0002395188,0.2863387],"genre_scores_gemma":[0.9164656,0.003011442,0.02681044,0.03725398,0.001050356,0.0009252222,0.0003703858,0.0002021813,0.01391026],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6988981,"threshold_uncertainty_score":0.8618658,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7165778147701756,"score_gpt":0.6718581571517968,"score_spread":0.04471965761837882,"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."}}