{"id":"W4207018799","doi":"10.1109/accc54619.2021.00032","title":"Adaptive Digital Encounters: An approach for reducing digital impact on outpatient flow","year":2021,"lang":"en","type":"article","venue":"","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute for Information and Communications Technology Promotion; Information Technology Research Centre; Ministry of Science and ICT, South Korea","keywords":"Computer science; Health care; Digital health; Process (computing); Service (business); Key (lock); Process management; Human–computer interaction; Computer security; Engineering; Operating system","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.001949011,0.0004845441,0.0003004894,0.001266634,0.0009076426,0.002347907,0.001259036,0.0007301724,0.008526471],"category_scores_gemma":[0.008730016,0.0002089058,0.0004549634,0.0007488125,0.0005884405,0.002230118,0.003167148,0.0007514445,0.001175914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005098675,"about_ca_system_score_gemma":0.001517328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005342044,"about_ca_topic_score_gemma":0.00122121,"domain_scores_codex":[0.9979874,0.0009842663,0.0001603872,0.0002071255,0.0005276085,0.000133247],"domain_scores_gemma":[0.9968007,0.001487099,0.0004094626,0.000479833,0.0003792041,0.00044378],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005787524,0.003660538,0.01570854,0.0006546444,0.00004717051,0.0002293154,0.005676165,0.0009965458,0.01638237,0.00681168,0.005352187,0.9439022],"study_design_scores_gemma":[0.001941363,0.02439931,0.255024,0.002114181,0.001027865,0.005924058,0.03537932,0.05638962,0.07123432,0.04199989,0.5039555,0.0006104864],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6371858,0.0008650709,0.2811206,0.004154313,0.00027637,0.002897543,0.0002811326,0.004129188,0.06908999],"genre_scores_gemma":[0.6976179,0.0005308545,0.2874399,0.0006468004,0.000133126,0.0009857098,0.0001763542,0.0001299083,0.01233942],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008526471,"threshold_uncertainty_score":0.02852392,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06334105322066544,"score_gpt":0.387808399744248,"score_spread":0.3244673465235826,"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."}}