{"id":"W2593322890","doi":"","title":"Personal Medical Information: Privacy or Personal Data Protection?","year":2006,"lang":"en","type":"article","venue":"eYLS (Yale Law School)","topic":"Patient Dignity and Privacy","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Personally identifiable information; Internet privacy; Business; Privacy protection; Information privacy; Medical information; Computer security; Computer science; Information retrieval","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004752419,0.0002063181,0.0002775848,0.00008960769,0.0002958775,0.00009879078,0.000451675,0.0002196087,0.008168627],"category_scores_gemma":[0.000888449,0.0001629559,0.00008422192,0.0002851546,0.0001648786,0.00140211,0.0003055379,0.0006577459,0.001573344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009933465,"about_ca_system_score_gemma":0.0006617852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001111003,"about_ca_topic_score_gemma":0.0002489181,"domain_scores_codex":[0.9976485,0.00007084738,0.0004469045,0.0003117128,0.001152809,0.000369182],"domain_scores_gemma":[0.9986561,0.00007276749,0.0001188492,0.0006054328,0.0001425807,0.000404288],"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":[0.007999169,0.004330665,0.09362508,0.002946002,0.0009439955,0.001283519,0.006524523,0.00001050843,0.0009888991,0.03164045,0.7526405,0.09706669],"study_design_scores_gemma":[0.00356151,0.0003702233,0.01964775,0.0002417961,0.00007657616,0.0005316263,0.0002053125,0.003241146,0.0001851035,0.0003607352,0.9712746,0.0003036246],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8795386,0.000611581,0.004130654,0.0239515,0.001148963,0.00232749,0.0005169268,0.0007373033,0.08703697],"genre_scores_gemma":[0.9869031,0.00002242446,0.00164835,0.005029329,0.001632938,0.0000612824,0.001393868,0.00002312924,0.003285606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2186341,"threshold_uncertainty_score":0.999204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05484248463691926,"score_gpt":0.2999532785987952,"score_spread":0.245110793961876,"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."}}