{"id":"W4322751754","doi":"10.2196/38430","title":"A Personalized Avatar-Based Web Application to Help People Understand How Social Distancing Can Reduce the Spread of COVID-19: Cross-sectional, Observational, Pre-Post Study","year":2023,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; University of Manitoba; Centre intégré de santé et de services sociaux de Chaudière-Appalaches; Université Laval","funders":"Canadian Institutes of Health Research; Canadian Immunization Research Network","keywords":"Social distance; Context (archaeology); Computer science; Internet privacy; World Wide Web; Psychology; Coronavirus disease 2019 (COVID-19); Medicine; Geography; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003383108,0.0001587574,0.0002128347,0.0003789571,0.001657154,0.0005830141,0.00124817,0.00007113935,0.00001439493],"category_scores_gemma":[0.0007777004,0.0001251214,0.00009044971,0.004075598,0.0003064207,0.0006072542,0.0004229868,0.0003321288,0.00004040604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007813373,"about_ca_system_score_gemma":0.001712269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000896915,"about_ca_topic_score_gemma":0.002284019,"domain_scores_codex":[0.996418,0.0005027486,0.0003700653,0.0004538831,0.00176074,0.0004945693],"domain_scores_gemma":[0.9966604,0.001183623,0.0001818572,0.0006495813,0.001049425,0.0002751021],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00109497,0.002725241,0.07995094,0.0008866916,0.0002800363,0.000005293527,0.427028,0.006015157,0.02397489,0.4020913,0.05150305,0.004444427],"study_design_scores_gemma":[0.001188726,0.0006139204,0.9135265,0.00001752516,0.000004033791,0.000002091919,0.02297895,0.05345707,0.0003765531,0.004223976,0.003391686,0.0002189697],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8211755,0.000007521945,0.1435564,0.03228845,0.00003969263,0.002365219,0.0002998537,0.0001170404,0.0001502508],"genre_scores_gemma":[0.9975833,0.000003745718,0.0001843052,0.0003362157,0.00006445462,0.001408281,0.0001364268,0.00001407933,0.0002691628],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8335755,"threshold_uncertainty_score":0.9996426,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2075031502922367,"score_gpt":0.4716033776729741,"score_spread":0.2641002273807374,"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."}}