{"id":"W4385703746","doi":"10.1016/j.eclinm.2023.102145","title":"Forming a consensus opinion to inform long COVID support mechanisms and interventions: a modified Delphi approach","year":2023,"lang":"en","type":"article","venue":"EClinicalMedicine","topic":"Long-Term Effects of COVID-19","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Likert scale; Psychological intervention; Medicine; Coronavirus disease 2019 (COVID-19); Delphi method; Delphi; Family medicine; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Computer-assisted web interviewing; 2019-20 coronavirus outbreak; Health care; Nursing; Political science; Psychology; Law; Marketing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003058888,0.0003201596,0.0008843029,0.0006108746,0.0001826552,0.00003225948,0.0002117952,0.0002497382,0.0001441917],"category_scores_gemma":[0.01003302,0.0002604116,0.0002753522,0.0008924063,0.0002227233,0.0001047847,0.000359695,0.0004620018,0.0002471059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001234312,"about_ca_system_score_gemma":0.0003011766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005457006,"about_ca_topic_score_gemma":0.00001513934,"domain_scores_codex":[0.9967998,0.0000824118,0.001237218,0.0006276623,0.0006631128,0.000589848],"domain_scores_gemma":[0.9959214,0.001923666,0.0002385175,0.0006705745,0.0001561062,0.001089686],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.02269143,0.005566689,0.09070554,0.06056299,0.004647306,0.009505522,0.02611542,0.001429324,0.007127083,0.07596578,0.4206753,0.2750076],"study_design_scores_gemma":[0.1597298,0.06681991,0.4298854,0.02992138,0.004873522,0.01041124,0.01308772,0.1241787,0.001283588,0.04595494,0.1077463,0.006107431],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6463583,0.0007051385,0.1849464,0.1439537,0.003004041,0.01016138,0.00008735758,0.002343976,0.00843975],"genre_scores_gemma":[0.9699685,0.0001694867,0.01257607,0.01408668,0.0005800624,0.0003065566,0.0004420321,0.00007576948,0.001794835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3391798,"threshold_uncertainty_score":0.9999848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1145251877016613,"score_gpt":0.4267155951725115,"score_spread":0.3121904074708503,"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."}}