{"id":"W4205155896","doi":"10.2196/preprints.21646","title":"COVID-19 and the Gendered Use of Emojis on Twitter: Infodemiology Study (Preprint)","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Digital Communication and Language","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Emoji; Coronavirus disease 2019 (COVID-19); Preprint; Psychology; Pandemic; Social media; Gender studies; Social psychology; Sociology; Political science; Medicine; Computer science; Law; World Wide Web","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"observational","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007121788,0.0001904709,0.0004184688,0.00008141601,0.00006188451,0.0002314721,0.002188349,0.0000986274,0.00005118522],"category_scores_gemma":[0.001417418,0.0001208035,0.0001015393,0.0001259004,0.000194992,0.0001114563,0.007462739,0.0004683304,0.00002115619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003685517,"about_ca_system_score_gemma":0.0001989184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008131004,"about_ca_topic_score_gemma":0.00009387515,"domain_scores_codex":[0.9980299,0.0006752756,0.0004362718,0.0005232599,0.0002056545,0.0001295687],"domain_scores_gemma":[0.9956158,0.001320845,0.0002644056,0.002567034,0.0000510851,0.00018082],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003890411,0.0008396636,0.0185517,0.0002920624,0.0005224145,0.00004081488,0.08250961,0.00380693,0.00001968648,0.8633608,0.01259833,0.01706898],"study_design_scores_gemma":[0.02207585,0.002764591,0.1660031,0.0002334492,0.0002690387,0.0001215073,0.01888241,0.2417241,0.0003291844,0.2856449,0.2581183,0.003833415],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3371192,0.0004856781,0.4086591,0.08343568,0.0004357227,0.006123672,0.0000373126,0.00106903,0.1626347],"genre_scores_gemma":[0.9757957,0.0000579034,0.003721511,0.0199543,0.000007830768,0.00005353988,0.000005935727,0.00000699781,0.0003962892],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6386765,"threshold_uncertainty_score":0.930177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1753729357837898,"score_gpt":0.3541404093141335,"score_spread":0.1787674735303437,"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."}}