{"id":"W4328029093","doi":"10.2196/44413","title":"Cross-sectional Analysis of Dermatologists and Sponsored Content on TikTok","year":2023,"lang":"en","type":"article","venue":"JMIR Dermatology","topic":"Social Media in Health Education","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cross-sectional study; Medicine; Pathology","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":[0.0009230825,0.0002710179,0.0002763518,0.001607203,0.0008812631,0.001037235,0.0004502954,0.0009001245,0.007348832],"category_scores_gemma":[0.003309845,0.00060718,0.0005718392,0.001973599,0.0003340938,0.000901659,0.000965639,0.001034708,0.001787832],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004614948,"about_ca_system_score_gemma":0.0006584593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01125065,"about_ca_topic_score_gemma":0.01607683,"domain_scores_codex":[0.9988111,0.0002904327,0.0001627408,0.000206962,0.0002273128,0.0003013773],"domain_scores_gemma":[0.9952148,0.0009795773,0.001900134,0.0002323937,0.0005869294,0.001086153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008733309,0.0002070545,0.9982927,0.00001449596,0.00005340103,0.00004092009,0.0004321801,0.000006277551,0.0001232762,0.00001050065,0.0001576778,0.0005741373],"study_design_scores_gemma":[0.000004033204,0.0001060203,0.9975355,0.00000571751,0.00001916039,0.00007387575,0.00204609,0.00002231332,0.00002151558,0.000004298789,0.0001585284,0.000002987018],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986843,0.00008367954,0.00002845747,0.00004661219,0.000009828987,0.00001770353,0.0005959288,0.000001874117,0.0005314691],"genre_scores_gemma":[0.9983134,0.00009664455,0.00004676493,0.00009305542,0.00001242262,0.00003634527,0.0006298769,0.000003443088,0.0007681317],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01125065,"threshold_uncertainty_score":0.02458429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2217920397442575,"score_gpt":0.4741823122892198,"score_spread":0.2523902725449623,"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."}}