{"id":"W3119393345","doi":"10.2196/23238","title":"A Patient Journey Map to Improve the Home Isolation Experience of Persons With Mild COVID-19: Design Research for Service Touchpoints of Artificial Intelligence in eHealth","year":2021,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"COVID-19 and Mental Health","field":"Psychology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"eHealth; Isolation (microbiology); Context (archaeology); Social isolation; Telehealth; Telemedicine; Patient experience; Coronavirus disease 2019 (COVID-19); Service (business); Health care; Psychology; Medicine; Nursing; Disease; Psychiatry; Business","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":[0.001950211,0.0001111832,0.0002598332,0.0001869208,0.0001317607,0.00001493038,0.0003004798,0.0001390164,0.0002835894],"category_scores_gemma":[0.0006592228,0.00007783035,0.00003827186,0.0008854537,0.0001872578,0.0001030681,0.0001156123,0.0003989208,0.0000178964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003354346,"about_ca_system_score_gemma":0.002867939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009941293,"about_ca_topic_score_gemma":0.001206504,"domain_scores_codex":[0.9972448,0.0002877951,0.0009861148,0.0001557108,0.0008727426,0.0004528101],"domain_scores_gemma":[0.9971258,0.001423781,0.0002461883,0.000374146,0.0003167295,0.000513342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.002141825,0.000836922,0.0007191653,0.002550966,0.00002526126,0.0000124254,0.92448,0.000195078,0.0001711101,0.006028189,0.002832678,0.06000638],"study_design_scores_gemma":[0.001757211,0.005760015,0.001812762,0.001009903,0.00001781687,0.00004743146,0.9155332,0.05629475,0.003802575,0.003206181,0.01038179,0.000376338],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7354486,0.0000830219,0.2458394,0.01472019,0.0004217122,0.003172591,0.00007218725,0.00001823042,0.0002240854],"genre_scores_gemma":[0.9787431,0.00002070102,0.009270804,0.01109563,0.00006279347,0.0007340732,0.00001649356,0.00001361428,0.00004279725],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2432945,"threshold_uncertainty_score":0.50876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2016153436869412,"score_gpt":0.5006381597003555,"score_spread":0.2990228160134143,"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."}}