{"id":"W4220868255","doi":"10.2196/36263","title":"Telehealth Services for Substance Use Disorders During the COVID-19 Pandemic: Longitudinal Assessment of Intensive Outpatient Programming and Data Collection Practices","year":2022,"lang":"en","type":"article","venue":"JMIR Mental Health","topic":"Telemedicine and Telehealth Implementation","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Telehealth; Pandemic; Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Data collection; Telemedicine; Substance use; Medicine; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Medical emergency; Psychiatry; Health care; Virology; Political science; Sociology","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":[0.0122569,0.000190019,0.0001978993,0.001007484,0.001065831,0.00117811,0.0006407953,0.0005647278,0.0008577008],"category_scores_gemma":[0.03647318,0.0003409064,0.0005351627,0.001157201,0.0005226556,0.001607319,0.001747835,0.001292371,0.0001833533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001424424,"about_ca_system_score_gemma":0.003050775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01746326,"about_ca_topic_score_gemma":0.02090233,"domain_scores_codex":[0.9941784,0.003287519,0.0006178267,0.0004040709,0.0008958209,0.0006163161],"domain_scores_gemma":[0.9736943,0.007320972,0.0114602,0.001849385,0.003282257,0.002392979],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008971988,0.0002660803,0.9904773,0.00001730662,0.00002083418,0.00002157301,0.001861893,0.00005024129,0.00008854725,0.0000280867,0.0002129093,0.006865501],"study_design_scores_gemma":[0.00001568926,0.0005502608,0.9933363,0.00004394027,0.00001511059,0.0000819795,0.00486019,0.0005365844,0.0001115838,0.00003382354,0.0004038075,0.00001073648],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9984689,0.00007562721,0.0002493192,0.0002784972,0.000005263083,0.0001403856,0.0003264864,0.000007073525,0.0004483652],"genre_scores_gemma":[0.9982332,0.0001065022,0.0006352042,0.000122822,0.000009160034,0.0002424937,0.0005103656,0.000003619153,0.0001366193],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01746326,"threshold_uncertainty_score":0.06482148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1438138711743696,"score_gpt":0.4819230223964648,"score_spread":0.3381091512220952,"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."}}