{"id":"W4396832557","doi":"10.1145/3613904.3642104","title":"Privacy in Immersive Extended Reality: Exploring User Perceptions, Concerns, and Coping Strategies","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Internet privacy; Perception; Computer science; Information privacy; Privacy software; Data collection; Coping (psychology); Mobile device; The Internet; World Wide Web; Psychology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0009806289,0.0002492472,0.0003290769,0.0002425653,0.0003626184,0.0008450244,0.0005140618,0.0003377365,0.0002401443],"category_scores_gemma":[0.0003146347,0.0002583069,0.00008027532,0.0002305694,0.0003098223,0.0007762071,0.002647161,0.0009584622,0.00004078859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003961078,"about_ca_system_score_gemma":0.0006807812,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05281137,"about_ca_topic_score_gemma":0.01348357,"domain_scores_codex":[0.9977782,0.0003432604,0.0003685751,0.0007414807,0.0003741134,0.0003943596],"domain_scores_gemma":[0.9991111,0.0001001608,0.0001061275,0.0004750135,0.00008135691,0.0001263115],"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":[0.00009025973,0.0001746263,0.003254531,0.002117679,0.0001980061,0.00009349313,0.3357972,0.00007999736,0.0006228646,0.6172539,0.01735814,0.02295934],"study_design_scores_gemma":[0.0004645373,0.00004964142,0.009697861,0.001223948,0.00009075517,0.000003122435,0.3713591,0.0002546465,0.0001390955,0.5689294,0.04681512,0.0009728288],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8862303,0.007621907,0.006702248,0.02807228,0.005363191,0.003663755,0.0002588015,0.000939682,0.06114785],"genre_scores_gemma":[0.9833646,0.01418229,0.0006635552,0.00009981942,0.0008898454,0.0002742738,0.00007380074,0.00002440648,0.0004273992],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09713433,"threshold_uncertainty_score":0.9999869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1351120763101951,"score_gpt":0.3836483550079312,"score_spread":0.2485362786977361,"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."}}