{"id":"W2403232321","doi":"10.1145/2858036.2858214","title":"Privacy Personas","year":2016,"lang":"en","type":"article","venue":"","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":98,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Categorization; Computer science; Cluster analysis; USable; Persona; Sample (material); Data science; Human–computer interaction; Usage data; Internet privacy; World Wide Web; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003475714,0.0004799254,0.0003891475,0.001410775,0.004160487,0.003904441,0.0009527249,0.001633433,0.02379787],"category_scores_gemma":[0.01054331,0.0003695466,0.0006507204,0.001641903,0.002129004,0.0065962,0.003597469,0.001777797,0.00632207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001488868,"about_ca_system_score_gemma":0.001363201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002405823,"about_ca_topic_score_gemma":0.001812726,"domain_scores_codex":[0.9943349,0.002400498,0.0004286791,0.0009999736,0.001331101,0.0005047946],"domain_scores_gemma":[0.9934016,0.00159548,0.0009550328,0.002813159,0.0008047852,0.0004298787],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002181846,0.000204306,0.01936246,0.000214325,0.00005984161,0.0005960761,0.02034845,0.001234103,0.003807935,0.7769026,0.02375096,0.1533008],"study_design_scores_gemma":[0.00003501603,0.0001710024,0.0105229,0.0002255896,0.00006933975,0.003839132,0.01071963,0.007553948,0.006372784,0.1784401,0.7819467,0.0001037836],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1779041,0.0016044,0.3281187,0.006946463,0.0003683682,0.001220667,0.002988155,0.003720194,0.477129],"genre_scores_gemma":[0.8666366,0.0008057278,0.06219046,0.001011096,0.00008578969,0.0005906259,0.001408102,0.0002038748,0.06706786],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02379787,"threshold_uncertainty_score":0.07961178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03917590944960503,"score_gpt":0.3124074547813513,"score_spread":0.2732315453317463,"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."}}