{"id":"W6986531413","doi":"","title":"Private Verification of Access on Medical Data: An Initial Study","year":2017,"lang":"en","type":"article","venue":"Open Repository and Bibliography (University of Luxembourg)","topic":"Intellectual Property and Patents","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Confidentiality; Government (linguistics); Key (lock); XACML; Matching (statistics); Measure (data warehouse)","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":[],"consensus_categories":[],"category_scores_codex":[0.03292688,0.000330238,0.0006915478,0.005049605,0.002550181,0.004836935,0.001293277,0.002056924,0.02587952],"category_scores_gemma":[0.3070219,0.000496153,0.0006561489,0.004181082,0.005369629,0.007436594,0.004093023,0.001403994,0.003471807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003994247,"about_ca_system_score_gemma":0.01117109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009111394,"about_ca_topic_score_gemma":0.00544973,"domain_scores_codex":[0.9524029,0.02322979,0.00357118,0.002532759,0.01524722,0.003016116],"domain_scores_gemma":[0.4094038,0.452869,0.02813718,0.03193602,0.07193348,0.005720529],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003816538,0.003171952,0.6974406,0.002770581,0.0002336293,0.003937051,0.05421145,0.001176285,0.001528915,0.02710189,0.01269532,0.1919157],"study_design_scores_gemma":[0.0005868963,0.004987491,0.7419543,0.003370193,0.0006393645,0.009937462,0.09504094,0.006631024,0.007222994,0.01859432,0.1108057,0.0002293497],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9551397,0.004172393,0.003357985,0.003809612,0.00009277397,0.0007317919,0.001924433,0.00004947341,0.03072186],"genre_scores_gemma":[0.9953342,0.0007942574,0.0004996386,0.000130394,0.00006180859,0.00006774861,0.000392071,0.00002487943,0.002694931],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03292688,"threshold_uncertainty_score":0.174136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2831927824997894,"score_gpt":0.3283661168649422,"score_spread":0.04517333436515281,"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."}}