{"id":"W4394988813","doi":"10.2196/43022","title":"Using a Smartphone-Based Chatbot for Postoperative Care After Intravitreal Injection During the COVID-19 Pandemic: Retrospective Cohort Study","year":2024,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Telemedicine and Telehealth Implementation","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; Chatbot; Medicine; Retrospective cohort study; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Cohort; Emergency medicine; Medical emergency; Virology; Surgery; Internal medicine; World Wide Web; Computer science; Disease; Infectious disease (medical specialty)","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":[0.001064489,0.0004154627,0.0005615352,0.0008802828,0.001099875,0.000985511,0.0005220006,0.0007293542,0.002452961],"category_scores_gemma":[0.003417445,0.0006245223,0.001136021,0.001278156,0.0004429167,0.001051896,0.000771566,0.001043122,0.0004325841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006627587,"about_ca_system_score_gemma":0.0009111662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01036914,"about_ca_topic_score_gemma":0.01163085,"domain_scores_codex":[0.9987611,0.0002274842,0.000215797,0.0003038002,0.0002519726,0.0002399841],"domain_scores_gemma":[0.9975958,0.0004041604,0.001077263,0.0002376868,0.0003872675,0.0002977027],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001440457,0.0001157985,0.9977731,0.00006212726,0.00006946605,0.0002100085,0.0003983088,0.0000112315,0.000114479,0.00001288806,0.0001396579,0.0009487845],"study_design_scores_gemma":[0.0000269833,0.0009545163,0.9937084,0.00008656208,0.000196061,0.0009491221,0.003135468,0.000255243,0.0000873953,0.0000209879,0.000556429,0.00002281585],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989383,0.0003506382,0.00008592352,0.00002220886,0.00000835808,0.00006953596,0.0002620069,0.000002036625,0.0002610259],"genre_scores_gemma":[0.9990643,0.0002445361,0.0001022639,0.00007762272,0.00001120103,0.0000749826,0.0002649621,0.000004566811,0.0001557136],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01036914,"threshold_uncertainty_score":0.0206176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1120955071983963,"score_gpt":0.4991088635213963,"score_spread":0.387013356323,"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."}}