{"id":"W3120829418","doi":"10.1016/s2589-7500(20)30315-0","title":"What social media told us in the time of COVID-19: a scoping review","year":2021,"lang":"en","type":"article","venue":"The Lancet Digital Health","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":695,"is_retracted":false,"has_abstract":true,"ca_institutions":"Seneca Polytechnic; University of Waterloo","funders":"","keywords":"Social media; Government (linguistics); Scarcity; Public health; Dissemination; Information Dissemination; Quality (philosophy)","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.002255633,0.00005217271,0.0002598024,0.00001639783,0.0002531751,0.0002093196,0.0002715783,0.00002592223,0.0001971392],"category_scores_gemma":[0.002159388,0.00003146027,0.00004279777,0.0004163949,0.0001240401,0.0008435961,0.00003143461,0.0001012409,0.00005152221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007201772,"about_ca_system_score_gemma":0.00180715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001413381,"about_ca_topic_score_gemma":0.00148801,"domain_scores_codex":[0.9986634,0.0003272624,0.0002795724,0.00006617604,0.0003894912,0.0002740922],"domain_scores_gemma":[0.998975,0.0005741816,0.0001563865,0.0001522591,0.00003779491,0.0001044027],"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":[0.00002964551,0.00009859977,0.000230016,0.00554061,0.00001103756,0.00000778406,0.6622006,0.000004577725,7.548488e-7,0.04988046,0.1822055,0.09979049],"study_design_scores_gemma":[0.002860219,0.0001509525,0.01141145,0.05054932,0.00002754446,0.00004536723,0.3246941,0.00005997463,0.00001997441,0.02683037,0.5826325,0.0007181796],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.04093355,0.03622063,0.00002583612,0.8131434,0.0004525066,0.001374203,0.00008930959,0.00007718506,0.1076834],"genre_scores_gemma":[0.5405515,0.09351695,0.0000245684,0.3642514,0.0009205234,0.00001037969,0.00007447795,0.00001053606,0.0006396992],"genre_candidate":"commentary","genre_consensus":null,"teacher_disagreement_score":0.499618,"threshold_uncertainty_score":0.3205806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1357369445448182,"score_gpt":0.4415830560809774,"score_spread":0.3058461115361591,"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."}}