{"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":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009548593,0.0001009067,0.000150596,0.0002026869,0.001894265,0.00008719328,0.0002185711,0.00001999591,0.001058586],"category_scores_gemma":[0.0001984156,0.0000962251,0.00002236807,0.0005795952,0.00003551042,0.0002893502,0.0001999088,0.0001492605,0.00001618859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003514828,"about_ca_system_score_gemma":0.0002693683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001398919,"about_ca_topic_score_gemma":0.001229446,"domain_scores_codex":[0.9985232,0.0002651871,0.0002241405,0.0001761859,0.0004227898,0.0003884712],"domain_scores_gemma":[0.9993128,0.00006657289,0.0001131195,0.000163095,0.00003383851,0.0003105443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.00004350157,0.00009957842,0.42054,0.00002475489,0.00004167828,0.0000192337,0.553336,0.02242589,0.0002577808,0.0000970343,0.002668021,0.00044656],"study_design_scores_gemma":[0.00193423,0.0002222905,0.4761758,0.00002031783,0.0000364412,0.00001349395,0.4704567,0.00114815,0.00002652964,0.0000254617,0.04945834,0.0004822632],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914812,0.0000122569,0.0009510283,0.001289578,0.0001212504,0.0007002647,0.000002762078,0.0000994511,0.005342201],"genre_scores_gemma":[0.9942783,0.000001543534,0.0002613644,0.004809774,0.00008404229,0.00003654573,0.000004089644,0.00001024604,0.0005141372],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08287928,"threshold_uncertainty_score":0.9998546,"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."}}