{"id":"W3207419215","doi":"10.2196/28146","title":"How Identification With the Social Environment and With the Government Guide the Use of the Official COVID-19 Contact Tracing App: Three Quantitative Survey Studies","year":2021,"lang":"en","type":"article","venue":"JMIR mhealth and uhealth","topic":"COVID-19 Digital Contact Tracing","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Contact tracing; Government (linguistics); Identification (biology); Internet privacy; Tracing; Coronavirus disease 2019 (COVID-19); Public relations; Social distance; Psychology; Political science; Computer science; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001843712,0.000214353,0.0002964589,0.0000187988,0.001709236,0.0004384963,0.0004431728,0.00004080336,5.151786e-7],"category_scores_gemma":[0.0003135772,0.00008923808,0.00004404187,0.0003394034,0.0004036307,0.0004160581,0.000279201,0.0002944542,3.900855e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003825533,"about_ca_system_score_gemma":0.0009297244,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008995237,"about_ca_topic_score_gemma":0.01901429,"domain_scores_codex":[0.9972011,0.0008079562,0.0003394954,0.0004698432,0.0008192151,0.0003623817],"domain_scores_gemma":[0.9958505,0.002750839,0.0005678496,0.000586868,0.000112458,0.000131461],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.003946052,0.00125331,0.1855999,0.006707144,0.001634974,0.0000793247,0.3957941,0.004396685,0.0009274241,0.279438,0.02089782,0.09932525],"study_design_scores_gemma":[0.0009980099,0.000492929,0.9716545,0.00009204397,0.0001010815,0.00002613543,0.01456924,0.002395784,0.0001052247,0.0002066335,0.00912133,0.0002371202],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7265781,0.001796711,0.1012902,0.1686278,0.0001069626,0.00145738,0.00008979561,0.00003360511,0.0000195001],"genre_scores_gemma":[0.9936729,0.000250416,0.0002582827,0.005560551,0.00004478083,0.00007740226,0.000003060865,0.00001246701,0.0001201414],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7860546,"threshold_uncertainty_score":0.9995904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1779999895592498,"score_gpt":0.3813739027278018,"score_spread":0.203373913168552,"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."}}