{"id":"W4388894103","doi":"10.1109/pst58708.2023.10320200","title":"User modelling for privacy-aware self-disclosure","year":2023,"lang":"en","type":"article","venue":"","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Nudge theory; Internet privacy; Computer science; Context (archaeology); Order (exchange); Personally identifiable information; Private information retrieval; Social media; Work (physics); Self-disclosure; Information privacy; Computer security; World Wide Web; Psychology; Business; Social psychology; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007486515,0.00008064948,0.00009684706,0.00007439451,0.0007216095,0.0001134215,0.0004279383,0.0001156856,0.000114846],"category_scores_gemma":[0.0002130504,0.0000748678,0.00006922607,0.0004020556,0.00003819702,0.0004126743,0.0001749394,0.00008316817,0.0002065199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005516061,"about_ca_system_score_gemma":0.0001038326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001389601,"about_ca_topic_score_gemma":0.0007590493,"domain_scores_codex":[0.99897,0.00006124741,0.0001312973,0.0002396048,0.0002518331,0.000346021],"domain_scores_gemma":[0.9994105,0.000104609,0.00003697398,0.000266281,0.00008790229,0.00009374531],"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":[0.00009945044,0.0003217216,0.005535549,0.0003047523,0.0001457528,0.00000962262,0.06835267,0.002089351,0.0001783731,0.339595,0.5727525,0.01061526],"study_design_scores_gemma":[0.0003648915,0.00003930758,0.0001834181,0.00001323726,0.0000197418,3.061181e-7,0.004285846,0.05639945,0.0002451775,0.08257974,0.8556226,0.0002463061],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1991076,0.0001780309,0.7151544,0.02878821,0.002759999,0.003860039,0.0002144908,0.007349591,0.04258761],"genre_scores_gemma":[0.9792026,0.0003855493,0.01073399,0.0002520804,0.001072482,0.000176799,0.00009743448,0.00002927854,0.008049787],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.780095,"threshold_uncertainty_score":0.555011,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0569804136144983,"score_gpt":0.3245671429772851,"score_spread":0.2675867293627868,"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."}}