{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001320029,0.0001561693,0.000424747,0.0005807147,0.00004497851,0.00005611157,0.0001216764,0.0001487554,0.0001723405],"category_scores_gemma":[0.0001276242,0.000147004,0.00004811757,0.0007455513,0.000144983,0.0003006978,0.0001769256,0.0002505244,0.0003467977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004230572,"about_ca_system_score_gemma":0.00007300766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001774609,"about_ca_topic_score_gemma":0.000328348,"domain_scores_codex":[0.9986541,0.000130343,0.0003201691,0.0003561547,0.0001087552,0.0004304632],"domain_scores_gemma":[0.9992146,0.0001087915,0.0000743248,0.0003688709,0.00004466462,0.0001886857],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007441917,0.0002371776,0.8705696,0.000309664,0.00006914254,0.00324195,0.0003186231,5.408853e-7,0.001738635,0.0009568654,0.05378179,0.0687016],"study_design_scores_gemma":[0.001705379,0.00003460943,0.9176838,0.00008096087,0.00001597563,0.001104,0.0002774505,0.001420463,0.0001075108,0.0002282975,0.07714907,0.0001925161],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861681,0.0002507222,0.00003532539,0.008303197,0.0002266632,0.0001812828,0.00003067109,0.000328076,0.004475894],"genre_scores_gemma":[0.9982881,0.00003238272,0.0001026049,0.0006604347,0.00005280078,0.0000651617,0.0004312905,0.0000283698,0.0003388792],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06850908,"threshold_uncertainty_score":0.5994649,"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."}}