{"id":"W3203663888","doi":"10.26443/mjm.v20i1.862","title":"COVID-19, Social Media, and Policy: Suggestions for Canada’s Health Messaging Response","year":2021,"lang":"en","type":"article","venue":"McGill Journal of Medicine","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"McGill University","keywords":"Coronavirus disease 2019 (COVID-19); Social media; Public relations; Medicine; 2019-20 coronavirus outbreak; Internet privacy; Text messaging; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Public opinion; Public health; Political science; Nursing; Virology; Computer science; Politics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.02391787,0.001545118,0.001448777,0.00453196,0.02368475,0.01926355,0.006701251,0.03491225,0.01840865],"category_scores_gemma":[0.06790856,0.000919594,0.002502531,0.005421904,0.0194324,0.01225896,0.008408989,0.0292895,0.002078946],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1349884,"about_ca_system_score_gemma":0.5427962,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9810174,"about_ca_topic_score_gemma":0.9888754,"domain_scores_codex":[0.9752222,0.006033255,0.001085038,0.001165613,0.009402243,0.007091573],"domain_scores_gemma":[0.9118378,0.03121009,0.002172876,0.0009073394,0.03139987,0.02247198],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005764018,0.00004773301,0.001146208,0.0004437711,0.00003195911,0.0002949192,0.005075343,0.0003230385,0.000149586,0.03675614,0.9362156,0.01945809],"study_design_scores_gemma":[0.0001436874,0.00005094402,0.003915185,0.002312549,0.0001027714,0.00009104535,0.02168128,0.0008841144,0.0002263249,0.01878095,0.9515284,0.0002827042],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0003494514,0.002648614,0.0001543002,0.9909157,0.002252916,0.00002682082,0.00008227845,0.00003095876,0.003538978],"genre_scores_gemma":[0.02315574,0.01130108,0.003444416,0.9425617,0.003926396,0.0001718831,0.0001874715,0.00007411485,0.01517714],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.8650116,"threshold_uncertainty_score":0.979414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0834056439316239,"score_gpt":0.4129746850992536,"score_spread":0.3295690411676297,"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."}}