{"id":"W4206066386","doi":"10.31219/osf.io/7hypj","title":"Public Health Communication and Engagement on Social Media during the COVID-19 Pandemic","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Social Media and Politics","field":"Social Sciences","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; McGill University","funders":"","keywords":"Government (linguistics); Pandemic; Social media; Public health; Health communication; Coronavirus disease 2019 (COVID-19); Public relations; Public engagement; Political science; Business; Medicine; Disease; Infectious disease (medical specialty); Nursing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002063363,0.0001447748,0.0002480961,0.00004957534,0.002741838,0.0002280348,0.0006089707,0.0002455091,0.0001806676],"category_scores_gemma":[0.00372997,0.0001176914,0.00007304736,0.0001343455,0.0006120928,0.00004126406,0.000596318,0.001016252,0.00001694559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008599238,"about_ca_system_score_gemma":0.001947376,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007764982,"about_ca_topic_score_gemma":0.01048109,"domain_scores_codex":[0.9960374,0.002520771,0.0002639286,0.0002544573,0.0005289852,0.0003944916],"domain_scores_gemma":[0.9968354,0.002145078,0.0002224002,0.0002553373,0.0000524267,0.0004893217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006732621,0.00003372931,0.01278477,0.0001322451,0.00004703018,8.176739e-7,0.7338913,0.000001168478,0.000002050384,0.2341686,0.01269154,0.006239987],"study_design_scores_gemma":[0.0004991305,0.00001864983,0.02308678,0.00002727823,0.00002861533,5.386905e-7,0.2046229,0.000009929512,0.0000020443,0.0666668,0.7046791,0.0003582239],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.2733669,0.0006802028,0.00007338441,0.7066064,0.001135748,0.001042332,0.00006441217,0.0003957646,0.01663484],"genre_scores_gemma":[0.9781746,0.00486842,0.00007388318,0.01522385,0.00136488,0.00008710137,0.00004871371,0.00001355405,0.0001450404],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7048076,"threshold_uncertainty_score":0.9988424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4876340151813782,"score_gpt":0.4541316848168128,"score_spread":0.0335023303645654,"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."}}