{"id":"W2089775818","doi":"10.1145/1542207.1542220","title":"Usability meets access control","year":2009,"lang":"en","type":"article","venue":"","topic":"Spam and Phishing Detection","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Usability; Computer science; Access control; Control (management); Human–computer interaction; Computer network; Artificial intelligence","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":[0.0001954783,0.00004523211,0.00005835031,0.0000242363,0.00005708013,0.0002198849,0.0005431552,0.00002634561,0.00003891415],"category_scores_gemma":[0.00003599394,0.00003618644,0.00002873758,0.0001602821,0.000008225553,0.000675964,0.00002888844,0.00004537398,0.00004031346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000015623,"about_ca_system_score_gemma":0.00001210615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004730832,"about_ca_topic_score_gemma":0.00001130112,"domain_scores_codex":[0.9995022,0.0000283201,0.00007855752,0.0001750513,0.00010961,0.000106216],"domain_scores_gemma":[0.9995638,0.00003982185,0.00001918602,0.0003029765,0.00002952154,0.00004471984],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00002419693,0.0002076463,0.008785207,0.000005920192,0.00001268087,0.000007697889,0.0002907632,0.0003518617,0.005218782,0.196349,0.00932144,0.7794248],"study_design_scores_gemma":[0.001267775,0.0003955942,0.657593,0.000008630314,0.000007615497,0.00002203939,0.000004063071,0.1591652,0.02311633,0.134227,0.02377694,0.0004158834],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03888803,0.00002455788,0.9266703,0.009587551,0.0004051896,0.00009158398,2.093635e-7,0.0003625556,0.02397006],"genre_scores_gemma":[0.9948891,0.000001039716,0.002759826,0.00217997,0.00005317779,0.000001461155,8.85025e-8,8.303687e-7,0.0001145224],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.956001,"threshold_uncertainty_score":0.2120355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01814312700292619,"score_gpt":0.2769034031250828,"score_spread":0.2587602761221566,"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."}}