{"id":"W2095204861","doi":"10.1145/1124772.1124893","title":"Keeping up appearances","year":2006,"lang":"en","type":"article","venue":"","topic":"Personal Information Management and User Behavior","field":"Decision Sciences","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Context (archaeology); Affect (linguistics); Scope (computer science); Task (project management); World Wide Web; Domain (mathematical analysis); Internet privacy; Human–computer interaction; Information sensitivity; Web browser; Information retrieval; Psychology; The Internet; Computer security; Communication; Engineering; Mathematics","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":[0.002067698,0.0003399054,0.0002785577,0.0005889539,0.001287855,0.001779657,0.0006155288,0.0008752258,0.009267059],"category_scores_gemma":[0.01322446,0.0002088925,0.0003726367,0.0003601484,0.0008890489,0.002189118,0.001363309,0.001033094,0.001799666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003830584,"about_ca_system_score_gemma":0.0002697053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001589093,"about_ca_topic_score_gemma":0.00143812,"domain_scores_codex":[0.9978182,0.0008502047,0.0001208895,0.0002741644,0.0006924295,0.0002441168],"domain_scores_gemma":[0.9927574,0.002421814,0.001434619,0.001426342,0.00122381,0.0007359945],"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":[0.001394047,0.0007326372,0.2773992,0.0007244454,0.0001470591,0.004317369,0.1354055,0.0007089701,0.03629455,0.02037685,0.02112996,0.5013694],"study_design_scores_gemma":[0.00007818649,0.001952807,0.393479,0.0004956258,0.0003396982,0.01208121,0.1144971,0.003483383,0.01146816,0.008386871,0.4534596,0.0002783735],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9332293,0.001072061,0.01185417,0.00114965,0.0002404743,0.00008524508,0.0002336746,0.0003417011,0.05179366],"genre_scores_gemma":[0.9853929,0.0002423216,0.002586504,0.0002659383,0.00004917891,0.00001980077,0.000122806,0.0000633581,0.01125715],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009267059,"threshold_uncertainty_score":0.03100139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3079140247982008,"score_gpt":0.449484996983338,"score_spread":0.1415709721851372,"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."}}