{"id":"W3153830039","doi":"10.71781/1912","title":"The right to privacy through the development of smart technologies : how our personal health data is affected","year":2020,"lang":"en","type":"dissertation","venue":"Open MIND","topic":"Patient Dignity and Privacy","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Government of Canada; United Nations","keywords":"Internet privacy; Personally identifiable information; Information privacy; Psychology; Computer science; Business; Computer security","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004199424,0.0002347776,0.0004583333,0.00004356614,0.0004458503,0.0001245288,0.002123946,0.000159685,0.0001068496],"category_scores_gemma":[0.000694756,0.0001281271,0.00005304713,0.0003426461,0.00003439258,0.0001455976,0.0008559091,0.0004569634,0.0001206749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006997028,"about_ca_system_score_gemma":0.001544438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004139444,"about_ca_topic_score_gemma":0.0006065847,"domain_scores_codex":[0.9983816,0.00008229425,0.0003550528,0.0004752695,0.0004432818,0.0002625527],"domain_scores_gemma":[0.9983908,0.0001007728,0.0003584839,0.0009757691,0.0001087711,0.00006539679],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008863679,0.0002162963,0.000152405,0.0003727024,0.0005721764,0.00001144327,0.1630164,5.017508e-8,0.0006251016,0.00002531623,0.1355893,0.6985325],"study_design_scores_gemma":[0.0004670605,0.0003014255,0.001957123,0.0006335363,0.00008927389,0.000003365269,0.0394087,0.00001407754,0.02404494,0.00004003102,0.9328681,0.00017234],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5686384,0.002961878,0.000171562,0.3964513,0.00102717,0.009544989,0.0008747989,0.00003739844,0.02029258],"genre_scores_gemma":[0.9157775,0.0004177897,0.04627655,0.001257681,0.0001485334,0.0002071856,0.01118062,0.00007968828,0.02465442],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7972789,"threshold_uncertainty_score":0.5224871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1723902840470044,"score_gpt":0.4049425137586041,"score_spread":0.2325522297115997,"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."}}