{"id":"W4306247772","doi":"10.2196/40977","title":"Outcomes of a Community Engagement and Information Gathering Program to Support Telephone-Based COVID-19 Contact Tracing: Descriptive Analysis","year":2022,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"COVID-19 Digital Contact Tracing","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Contact tracing; Phone; Tracing; Telephone number; Telephone line; Computer science; Coronavirus disease 2019 (COVID-19); Medical emergency; Telecommunications; Medicine; Telephone network; Infectious disease (medical specialty); Computer network","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004085886,0.0003847545,0.0004662359,0.002885242,0.0007742373,0.00109364,0.001255527,0.0006151619,0.002403135],"category_scores_gemma":[0.01621477,0.0002656729,0.001262326,0.002577762,0.0004592495,0.001530493,0.001873557,0.001203928,0.0003202891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002478658,"about_ca_system_score_gemma":0.003668883,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02896713,"about_ca_topic_score_gemma":0.02690594,"domain_scores_codex":[0.9967565,0.0007543745,0.0004897516,0.0003444754,0.001042811,0.0006120739],"domain_scores_gemma":[0.9830551,0.004095498,0.007580669,0.0004823364,0.002909826,0.001876657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003628821,0.0006292111,0.9907863,0.0001014112,0.000110759,0.00003783457,0.0007041217,0.0002161749,0.00005143328,0.00005487087,0.0008501992,0.006094741],"study_design_scores_gemma":[0.00002322105,0.0006139608,0.9960956,0.00005060203,0.00005265017,0.00003853471,0.002102118,0.0005777708,0.00005191672,0.00003128789,0.0003501611,0.00001218622],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933488,0.0001022072,0.0002122904,0.0001206276,0.000009339627,0.0003832157,0.004468735,0.00001828929,0.001336555],"genre_scores_gemma":[0.995441,0.0001097834,0.0002466269,0.00005330244,0.00001264859,0.0007747121,0.00288296,0.000008577255,0.0004703968],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02896713,"threshold_uncertainty_score":0.05759698,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09774843044943088,"score_gpt":0.3499499145585221,"score_spread":0.2522014841090913,"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."}}