{"id":"W4416142963","doi":"10.69554/bzbz5748","title":"AI-driven surveillance in India: Reconciling privacy, national security and legal oversight","year":2025,"lang":"en","type":"article","venue":"Journal of data protection & privacy.","topic":"COVID-19 Digital Contact Tracing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"National security; Data Protection Act 1998; State (computer science); Electronic surveillance; European union; Disadvantage; Work (physics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001591695,0.0001432186,0.0002631459,0.0005438778,0.0001164195,0.0004534555,0.001498581,0.0000897277,0.000004106823],"category_scores_gemma":[0.001464155,0.0001425526,0.00004941114,0.0007384155,0.00003181905,0.005933832,0.001308577,0.0006844738,0.000002658912],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004014935,"about_ca_system_score_gemma":0.0008909912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006956713,"about_ca_topic_score_gemma":0.00006888414,"domain_scores_codex":[0.9981421,0.0001538561,0.0006066973,0.0003913397,0.0005013617,0.0002045941],"domain_scores_gemma":[0.9984297,0.0002441914,0.0003866467,0.000545043,0.0003169662,0.00007751507],"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":[0.002645606,0.002998571,0.3308299,0.003376462,0.001722225,0.002356221,0.009616905,0.004618516,0.02860333,0.1929194,0.03407225,0.3862406],"study_design_scores_gemma":[0.008382046,0.0008122306,0.3450307,0.001980668,0.00004037345,0.001487672,0.0001599258,0.2615165,0.004535914,0.06084368,0.3138911,0.001319199],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3135856,0.0007754198,0.6584423,0.02269779,0.001380644,0.0009361893,0.0000734311,0.0001237505,0.001984957],"genre_scores_gemma":[0.9933563,0.00004471117,0.005705783,0.0007478157,0.0001049847,0.000004080332,0.000005078902,0.000005495764,0.00002576811],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6797707,"threshold_uncertainty_score":0.5813127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04022657889226181,"score_gpt":0.3140550017510006,"score_spread":0.2738284228587388,"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."}}