{"id":"W1982333844","doi":"10.1177/0165551505055400","title":"How much is too little? Privacy and smart cards in Hong Kong and Ontario","year":2005,"lang":"en","type":"article","venue":"Journal of Information Science","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Conceptualization; Identity (music); Internet privacy; ICTS; China; Sociology; Focus (optics); Information privacy; Public relations; Information and Communications Technology; Political science; Business; Computer science; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001339383,0.0002382024,0.0004705646,0.0009438337,0.01047102,0.003614735,0.0008415014,0.0005407304,0.002247635],"category_scores_gemma":[0.003875266,0.0004001861,0.0003695379,0.004981539,0.004867995,0.001360587,0.002291332,0.001088192,0.0001472406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.09527217,"about_ca_system_score_gemma":0.09114854,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.996796,"about_ca_topic_score_gemma":0.9986166,"domain_scores_codex":[0.9982158,0.0003113618,0.0001102267,0.0001737686,0.000353393,0.0008355104],"domain_scores_gemma":[0.9945123,0.001180809,0.0009343392,0.000294202,0.001717761,0.001360546],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006066997,0.0002034251,0.6296295,0.0002741309,0.0001061797,0.002859729,0.2990412,0.0007485413,0.001155574,0.02808503,0.006580728,0.03070925],"study_design_scores_gemma":[0.00008277396,0.00009073739,0.5610486,0.0002245207,0.00009118187,0.0003095125,0.3888817,0.001073567,0.0005729985,0.001123581,0.04635664,0.000144102],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9869889,0.0005244195,0.00009145476,0.001929125,0.00001530857,0.00003938277,0.0002252237,0.000003607559,0.01018249],"genre_scores_gemma":[0.9932731,0.0007522173,0.0001647309,0.0002962581,0.000004156655,0.00002473289,0.0001143294,0.000005127176,0.005365219],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09527217,"threshold_uncertainty_score":0.6912512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02259539456538074,"score_gpt":0.2899245693904535,"score_spread":0.2673291748250727,"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."}}