{"id":"W4402722801","doi":"10.2196/53340","title":"Survey of Citizens’ Preferences for Combined Contact Tracing App Features During a Pandemic: Conjoint Analysis","year":2024,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"COVID-19 Digital Contact Tracing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Contact tracing; Conjoint analysis; Government (linguistics); Public health; Pandemic; Internet privacy; Public relations; Psychology; Business; Infectious disease (medical specialty); Medicine; Political science; Computer science; Coronavirus disease 2019 (COVID-19); Disease; Nursing; Economics","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":[],"consensus_categories":[],"category_scores_codex":[0.002626732,0.0002423063,0.0007605793,0.0005047644,0.0001921726,0.0006935173,0.0004511572,0.00009602971,0.000003825215],"category_scores_gemma":[0.0006967075,0.0002125412,0.0001652779,0.00166447,0.00004837898,0.0006259545,0.0001342358,0.0002214862,0.000001089658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000127955,"about_ca_system_score_gemma":0.001018101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008172372,"about_ca_topic_score_gemma":0.003554744,"domain_scores_codex":[0.9972537,0.0003404923,0.0006836021,0.0007217647,0.0003319263,0.0006685791],"domain_scores_gemma":[0.996486,0.002142678,0.0002168552,0.0004395689,0.0002662087,0.0004486722],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001158759,0.00008563975,0.9032003,0.003117102,0.00049879,0.000008826929,0.002994785,0.00002912472,0.000151978,0.006409763,0.0003910707,0.08299672],"study_design_scores_gemma":[0.0005760541,0.000322627,0.9837312,0.0000726073,0.000002585483,0.000007660869,0.00006560526,0.01422993,0.00001225282,0.0002070766,0.0005207458,0.0002517043],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9131906,0.003735247,0.07831737,0.002548342,0.000279532,0.0009308911,0.0002399139,0.0005114755,0.0002465925],"genre_scores_gemma":[0.9988155,0.000131361,0.00032856,0.0004249049,0.00003109009,0.00009686232,0.00006726254,0.00001455869,0.00008994631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08562483,"threshold_uncertainty_score":0.8667178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05886410740923942,"score_gpt":0.3300161935496939,"score_spread":0.2711520861404545,"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."}}