{"id":"W4310370637","doi":"10.2196/39849","title":"Identifying Profiles and Symptoms of Patients With Long COVID in France: Data Mining Infodemiology Study Based on Social Media","year":2022,"lang":"en","type":"article","venue":"JMIR Infodemiology","topic":"Long-Term Effects of COVID-19","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Social media; Coronavirus disease 2019 (COVID-19); Anxiety; Medicine; Psychology; Psychiatry; Computer science; World Wide Web; Disease; Pathology","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":[0.001782501,0.0002809558,0.001011321,0.0004862861,0.0001678713,0.000007007268,0.0004967796,0.0001897707,0.00008646576],"category_scores_gemma":[0.002856951,0.0002405071,0.00004436115,0.0003686163,0.000359671,0.0001431738,0.0008744198,0.0007035736,0.000001923381],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001691224,"about_ca_system_score_gemma":0.0003559083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007332314,"about_ca_topic_score_gemma":0.00006537735,"domain_scores_codex":[0.9966532,0.0009853124,0.0007747496,0.0006956891,0.0004302208,0.0004608201],"domain_scores_gemma":[0.99455,0.003987636,0.0004976147,0.0007418972,0.00008212129,0.0001406631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001608119,0.0006427102,0.9908277,0.0003195777,0.00006687264,0.00008152896,0.003908726,0.0005369882,0.00001474943,0.0000417593,0.0003474621,0.001603792],"study_design_scores_gemma":[0.008734069,0.002695266,0.9846955,0.00007834457,0.00007635356,0.000007529631,0.0007078202,0.00264581,0.000002746477,0.00004514054,0.0001021053,0.0002093444],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965798,0.00007372758,0.0001130765,0.0006531768,0.0001962278,0.002140294,0.0001332276,0.00006097207,0.00004949282],"genre_scores_gemma":[0.9950631,0.000001897711,0.0005588116,0.00311068,0.00007898545,0.0005650834,0.0005828685,0.00003202953,0.000006574511],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00712595,"threshold_uncertainty_score":0.9807593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04400189608833391,"score_gpt":0.3651983879838027,"score_spread":0.3211964918954688,"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."}}