{"id":"W4285047970","doi":"10.2196/39157","title":"COVID-Bot, an Intelligent System for COVID-19 Vaccination Screening: Design and Development","year":2022,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"AI in Service Interactions","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Chatbot; Usability; Coronavirus disease 2019 (COVID-19); Computer science; Reliability (semiconductor); Avatar; Artifact (error); Human–computer interaction; Artificial intelligence; Medicine; Infectious disease (medical specialty); Disease","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":[0.00254221,0.0007851083,0.0004283803,0.0007222711,0.0004230459,0.001048597,0.001760836,0.001008831,0.004807546],"category_scores_gemma":[0.004142939,0.0005442431,0.0004569366,0.0002519565,0.0005300688,0.001157709,0.0008707536,0.0007007479,0.001574553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005287101,"about_ca_system_score_gemma":0.001485937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001303465,"about_ca_topic_score_gemma":0.001523786,"domain_scores_codex":[0.9989034,0.0003340351,0.000099365,0.0002252386,0.0003544295,0.00008361827],"domain_scores_gemma":[0.9981307,0.0007159386,0.0001409312,0.00015226,0.0006383075,0.0002218404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002238847,0.001475321,0.02302834,0.003166794,0.0002183342,0.001845655,0.004827479,0.01372262,0.2331502,0.01021125,0.03204849,0.6740666],"study_design_scores_gemma":[0.001274965,0.01115549,0.04843167,0.001079754,0.0009917995,0.006892148,0.001795104,0.3873582,0.1921037,0.007804274,0.3404883,0.0006245414],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08000869,0.0005518486,0.877992,0.0006106692,0.0001942228,0.004634411,0.0004903083,0.02553754,0.009980211],"genre_scores_gemma":[0.2187473,0.0004649692,0.7612823,0.0004782365,0.00004265847,0.003134864,0.00095159,0.001187452,0.01371059],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004807546,"threshold_uncertainty_score":0.01608282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2356505457497943,"score_gpt":0.4679280276485589,"score_spread":0.2322774818987646,"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."}}