{"id":"W4393016617","doi":"10.2196/47154","title":"Short- and Long-Term Predicted and Witnessed Consequences of Digital Surveillance During the COVID-19 Pandemic: Scoping Review","year":2024,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"COVID-19 Digital Contact Tracing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University; Western University","funders":"","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); Term (time); 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Data science; Internet privacy; Computer science; Virology; Medicine; Outbreak; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001909376,0.00025906,0.0005701276,0.0001391905,0.0002998176,0.0009997333,0.0004161889,0.00006862129,0.000003461741],"category_scores_gemma":[0.001054553,0.0001920884,0.0000482691,0.0007214533,0.000430651,0.001202745,0.0003361743,0.0002392033,6.430932e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001082447,"about_ca_system_score_gemma":0.001649617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003174776,"about_ca_topic_score_gemma":0.0002475911,"domain_scores_codex":[0.997349,0.0002876824,0.0006840228,0.0007407291,0.0003709448,0.0005676712],"domain_scores_gemma":[0.9970026,0.001558135,0.0001641094,0.0004628638,0.0001046283,0.0007076895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001048917,0.0000139119,0.9422191,0.02793306,0.0000228868,0.00002882183,0.0005114053,7.812542e-7,0.00002563333,0.0009295274,0.00005594788,0.02824844],"study_design_scores_gemma":[0.0008949787,0.0003031952,0.9792012,0.01076088,0.000002417875,0.001395133,0.00006642799,0.001695309,0.000003699302,0.0003460415,0.004508337,0.0008223772],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7554932,0.1925726,0.01183211,0.03710996,0.0002267966,0.001993513,0.000121562,0.0005661917,0.000084013],"genre_scores_gemma":[0.9741613,0.02248805,0.00003099987,0.003140283,0.0000408965,0.00007852579,0.00001669429,0.00001432279,0.00002892632],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2186681,"threshold_uncertainty_score":0.9640452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07641700763838873,"score_gpt":0.3648599818637443,"score_spread":0.2884429742253556,"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."}}