{"id":"W4220942233","doi":"10.2196/35677","title":"Using Twitter to Examine Stigma Against People With Dementia During COVID-19: Infodemiology Study","year":2022,"lang":"en","type":"article","venue":"JMIR Aging","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Dementia Research Alliance; University of Toronto; University Health Network; Toronto Rehabilitation Institute; University of Waterloo; University of Ottawa; University of Alberta; University of Saskatchewan","funders":"Canadian Institutes of Health Research; Alzheimer Society; Saskatchewan Health Research Foundation; Consortium canadien en neurodégénérescence associée au vieillissement","keywords":"Dementia; Misinformation; Stigma (botany); Public health; Pejorative; Social media; Thematic analysis; Pandemic; Social distance; Psychology; Social stigma; Psychiatry; Medicine; Coronavirus disease 2019 (COVID-19); Nursing; Qualitative research; Political science; Sociology; Family medicine; Disease","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001833463,0.0003301209,0.000411779,0.001645804,0.002895868,0.002090327,0.0004232629,0.001073146,0.004121366],"category_scores_gemma":[0.01199587,0.0003200754,0.0005431866,0.001959351,0.0008956536,0.004281948,0.002873425,0.00151926,0.001408892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001920186,"about_ca_system_score_gemma":0.001695174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01006443,"about_ca_topic_score_gemma":0.01529119,"domain_scores_codex":[0.9985276,0.0007157726,0.0001410962,0.0001359302,0.0002013283,0.0002782852],"domain_scores_gemma":[0.9935316,0.002823408,0.001531351,0.0003537848,0.001023146,0.000736604],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0005658304,0.0007625232,0.4505553,0.001937766,0.0001356389,0.002018432,0.4647008,0.0001032024,0.0009390746,0.002702213,0.01933394,0.05624532],"study_design_scores_gemma":[0.00007067554,0.0004143576,0.3594691,0.001502771,0.0001499963,0.001044812,0.5825389,0.0006930752,0.0007846668,0.00126481,0.05195104,0.0001157611],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9847969,0.0006540192,0.0003422633,0.002720639,0.0001126443,0.0003357311,0.003043367,0.00001389099,0.007980563],"genre_scores_gemma":[0.9899538,0.001424648,0.0006945275,0.002198545,0.0001651013,0.001101995,0.001524733,0.00003144271,0.002905292],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01006443,"threshold_uncertainty_score":0.02001166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07267172906404393,"score_gpt":0.3827827364300702,"score_spread":0.3101110073660263,"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."}}