{"id":"W3015578022","doi":"10.1007/s10676-020-09572-w","title":"Give more data, awareness and control to individual citizens, and they will help COVID-19 containment","year":2021,"lang":"en","type":"preprint","venue":"Ethics and Information Technology","topic":"COVID-19 Digital Contact Tracing","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Università di Pisa; European Commission","keywords":"Contact tracing; Location data; Computer science; Tracing; Internet privacy; Computer security; Order (exchange); Coronavirus disease 2019 (COVID-19); Data collection; Control (management); Business; Infectious disease (medical specialty); 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":[0.005535238,0.001269626,0.001057402,0.002120111,0.002068981,0.008591596,0.004033439,0.008148877,0.08921294],"category_scores_gemma":[0.03798088,0.0007879997,0.001869968,0.002003924,0.001844089,0.02308649,0.006255071,0.006771114,0.07691353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002166771,"about_ca_system_score_gemma":0.005810953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01644097,"about_ca_topic_score_gemma":0.02146573,"domain_scores_codex":[0.993616,0.001792226,0.0003916436,0.001245053,0.002304132,0.0006509071],"domain_scores_gemma":[0.9606761,0.00755281,0.00193397,0.007492537,0.01718946,0.005155243],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001009606,0.0001926688,0.002989334,0.001078194,0.00007331373,0.0001368446,0.0005203868,0.0005337112,0.002896631,0.01997771,0.6564385,0.3150617],"study_design_scores_gemma":[0.00003770206,0.00003922084,0.001197633,0.0006471702,0.00004950538,0.0001245444,0.0007631475,0.001342559,0.001213306,0.01472952,0.9797861,0.00006948179],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.006646778,0.02435119,0.1908276,0.5298288,0.02972946,0.001537864,0.01332838,0.01371082,0.1900391],"genre_scores_gemma":[0.0985379,0.05146471,0.2711041,0.2378496,0.01731953,0.001482274,0.02005618,0.003459096,0.2987266],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.08921294,"threshold_uncertainty_score":0.298447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05212799996597137,"score_gpt":0.3382480121984986,"score_spread":0.2861200122325272,"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."}}