{"id":"W2511870452","doi":"10.1109/mpot.2016.2569726","title":"Privacy in Public","year":2016,"lang":"en","type":"article","venue":"IEEE Potentials","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Dystopia; Internet privacy; Action (physics); Reading (process); Value (mathematics); Computer security; Information privacy; Computer science; Political science; Law; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01155796,0.0006612921,0.0008444766,0.001331904,0.005976017,0.01665124,0.001719788,0.009547956,0.03864234],"category_scores_gemma":[0.0304306,0.0005707891,0.0009783561,0.00212921,0.01378072,0.02332317,0.008424908,0.01019908,0.009552246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005088486,"about_ca_system_score_gemma":0.007880874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003755128,"about_ca_topic_score_gemma":0.001982167,"domain_scores_codex":[0.9888542,0.004614981,0.0004559127,0.001983776,0.002753044,0.001337989],"domain_scores_gemma":[0.9823402,0.007851794,0.0008920579,0.006296042,0.001877146,0.0007426957],"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":[0.00001664028,0.00000900229,0.0001608536,0.00004595757,0.000008902885,0.00007273482,0.0006835036,0.0001899222,0.0000715544,0.9494855,0.03602397,0.01323128],"study_design_scores_gemma":[0.00001021828,0.00001550373,0.0001594311,0.0002207217,0.00001226968,0.0002359393,0.0005215188,0.0005088422,0.0003346963,0.6325369,0.365426,0.00001791329],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"commentary","genre_scores_codex":[0.00503234,0.01133791,0.06175265,0.1913291,0.002721895,0.0001101168,0.0008708716,0.0005712383,0.7262738],"genre_scores_gemma":[0.6503625,0.01583083,0.01520297,0.07954478,0.005918354,0.0004031306,0.001314759,0.0006040757,0.2308186],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.03864234,"threshold_uncertainty_score":0.1292715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05597693805940404,"score_gpt":0.318779274490906,"score_spread":0.262802336431502,"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."}}