{"id":"W4286741957","doi":"10.31235/osf.io/pnm9q","title":"White Paper - Rule of Law, Legitimacy and Effective COVID-19 Control Technologies","year":2022,"lang":"en","type":"preprint","venue":"","topic":"COVID-19 Digital Contact Tracing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute on Governance","funders":"","keywords":"Legitimacy; Rule of law; White paper; Empowerment; Set (abstract data type); Coronavirus disease 2019 (COVID-19); Political science; Perspective (graphical); Control (management); Law and economics; Law; Sociology; Computer science; Politics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005423006,0.0003936615,0.000675737,0.0003069968,0.0001841688,0.0004996462,0.001767063,0.0002299486,0.00008387249],"category_scores_gemma":[0.0005614639,0.0003726754,0.0001891261,0.0002553365,0.0002548057,0.0009111821,0.006114195,0.0007612186,0.000006031517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003796885,"about_ca_system_score_gemma":0.0004770751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0010825,"about_ca_topic_score_gemma":0.0001280379,"domain_scores_codex":[0.9975021,0.0001532321,0.0004342179,0.001084598,0.000456432,0.0003694563],"domain_scores_gemma":[0.9967265,0.001360898,0.0002881694,0.001395499,0.00009916813,0.0001297352],"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":[0.0001479842,0.0003001801,0.01091211,0.002795923,0.0005371974,0.0002452182,0.003903749,0.007314108,0.001142795,0.9177357,0.0009567484,0.05400831],"study_design_scores_gemma":[0.01191408,0.00198499,0.02066786,0.0008425727,0.0003866297,0.0001920606,0.002884926,0.05070674,0.006824241,0.74877,0.1490198,0.005806106],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01130233,0.001576176,0.8943384,0.01744731,0.0007809098,0.003852935,0.00020643,0.003912029,0.06658349],"genre_scores_gemma":[0.9898944,0.00002483521,0.005083766,0.00428615,0.00001605019,0.0004644243,0.000008745137,0.00002177796,0.0001998065],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9785921,"threshold_uncertainty_score":0.9998725,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01802058315680744,"score_gpt":0.2907239260662435,"score_spread":0.2727033429094361,"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."}}