{"id":"W3194599758","doi":"10.2196/26868","title":"COVID-19 Mask Usage and Social Distancing in Social Media Images: Large-scale Deep Learning Analysis","year":2021,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Infection Control and Ventilation","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Indraprastha Institute of Information Technology, Delhi","keywords":"Social distance; Coronavirus disease 2019 (COVID-19); Social media; Scale (ratio); 2019-20 coronavirus outbreak; Pandemic; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Internet privacy; Distancing; Computer science; Psychology; Virology; Medicine; Geography; World Wide Web; Outbreak; Infectious disease (medical specialty); Cartography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009408689,0.001142087,0.0006157872,0.00182582,0.0005239709,0.001043497,0.000711882,0.0009182632,0.001641299],"category_scores_gemma":[0.003742025,0.0002483378,0.0009954514,0.001121398,0.0004771916,0.001041243,0.001030999,0.001486542,0.000964035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008225192,"about_ca_system_score_gemma":0.0005656128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01242289,"about_ca_topic_score_gemma":0.01736899,"domain_scores_codex":[0.9993715,0.0001848666,0.00003689569,0.0001672986,0.00009850585,0.0001409471],"domain_scores_gemma":[0.9989159,0.0005720778,0.0001500257,0.0001045185,0.0001655243,0.00009200161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001534493,0.00212012,0.3473978,0.0007073912,0.0007856523,0.0009682599,0.001263133,0.05566324,0.00782114,0.001562635,0.05463007,0.525546],"study_design_scores_gemma":[0.00004712547,0.0003104529,0.1098823,0.0001453595,0.0001631888,0.0002766468,0.001271574,0.8746972,0.002699371,0.00320953,0.007225034,0.00007218918],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9560676,0.002697624,0.02517501,0.001911282,0.0003696273,0.0002776583,0.006962581,0.001192548,0.005346025],"genre_scores_gemma":[0.9717036,0.0006366218,0.01543471,0.0003262458,0.0001517325,0.0001579425,0.009120434,0.00004627303,0.002422518],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01242289,"threshold_uncertainty_score":0.02470118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02372295519846393,"score_gpt":0.3269946944080659,"score_spread":0.3032717392096019,"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."}}