{"id":"W4226312101","doi":"10.1186/s12906-022-03586-1","title":"Tracking discussions of complementary, alternative, and integrative medicine in the context of the COVID-19 pandemic: a month-by-month sentiment analysis of Twitter data","year":2022,"lang":"en","type":"article","venue":"BMC Complementary Medicine and Therapies","topic":"Complementary and Alternative Medicine Studies","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; Impact","funders":"McMaster University","keywords":"Coronavirus disease 2019 (COVID-19); Pandemic; Tracking (education); Context (archaeology); Sentiment analysis; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Data science; Computer science; Psychology; Medicine; History; Artificial intelligence; Virology; Infectious disease (medical specialty); Internal medicine; Outbreak","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001924288,0.0003315342,0.001278123,0.0004692206,0.0003281441,0.000003534195,0.0006776713,0.00001015846,0.001784592],"category_scores_gemma":[0.0001832344,0.0001535232,0.0001227558,0.0008882762,0.001607865,0.0000837659,0.0007783748,0.0003197098,4.042562e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008222216,"about_ca_system_score_gemma":0.00005521378,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01935408,"about_ca_topic_score_gemma":0.01113026,"domain_scores_codex":[0.9963114,0.0007638757,0.001196929,0.0004912717,0.0009805325,0.0002559903],"domain_scores_gemma":[0.9967458,0.00165443,0.0006653923,0.0007405449,0.00009108146,0.0001027766],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0006234226,0.0004206561,0.8566379,0.000153859,0.003404178,0.000009166321,0.1231577,0.00001724241,0.002688876,0.0005629973,0.00828064,0.004043427],"study_design_scores_gemma":[0.01385879,0.003381452,0.19134,0.0004139184,0.003988815,0.0000491674,0.749887,0.0006369806,0.0002861251,0.0009671007,0.03497262,0.0002179917],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9592645,0.007216806,0.0007053488,0.02966673,0.0001488475,0.001349048,0.001484531,0.000006910715,0.0001572438],"genre_scores_gemma":[0.9936612,0.0009415013,0.000145573,0.003982174,0.00009031381,0.00006186934,0.001069092,0.00001256849,0.00003572339],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6652979,"threshold_uncertainty_score":0.9991279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.219379062072292,"score_gpt":0.4169298314866801,"score_spread":0.197550769414388,"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."}}