{"id":"W4386228223","doi":"10.2196/48827","title":"Assessing Public Interest in Mpox via Google Trends, YouTube, and TikTok","year":2023,"lang":"en","type":"article","venue":"JMIR Dermatology","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Public interest; Internet privacy; World Wide Web; Advertising; Geography; Business; Computer science; Political science; Law","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":[0.001228008,0.0002586986,0.0002311842,0.006044653,0.0004633097,0.001319356,0.0003439135,0.0004477988,0.002483729],"category_scores_gemma":[0.006539637,0.0001250436,0.0003917143,0.004293974,0.0002039023,0.00150418,0.001043454,0.0005966904,0.0009153329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006042612,"about_ca_system_score_gemma":0.0008541954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03283907,"about_ca_topic_score_gemma":0.05287664,"domain_scores_codex":[0.9991441,0.0001833908,0.0001298274,0.0001287198,0.0002717247,0.0001422621],"domain_scores_gemma":[0.9940115,0.001711742,0.002348417,0.0001821159,0.001173637,0.0005725674],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002274675,0.0001304757,0.966151,0.0003019799,0.00009794122,0.0002074444,0.001478794,0.0003051383,0.0005352923,0.0003273926,0.005949604,0.02428745],"study_design_scores_gemma":[0.0000134627,0.0002358757,0.9804786,0.000127675,0.0000779499,0.00025074,0.005301018,0.003539115,0.0006877369,0.0001413309,0.009120014,0.00002648255],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9589642,0.0004205305,0.0002864915,0.0006317451,0.00003192612,0.0001677808,0.03179312,0.00008020838,0.007624085],"genre_scores_gemma":[0.9763393,0.0004908501,0.001347532,0.0001566253,0.0000594342,0.0001949917,0.01809145,0.00002327392,0.003296521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03283907,"threshold_uncertainty_score":0.06529582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08377668053887982,"score_gpt":0.3629836785624069,"score_spread":0.2792069980235271,"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."}}