{"id":"W4387027641","doi":"10.2196/50011","title":"A Social Media Analysis of Pemphigus","year":2023,"lang":"en","type":"article","venue":"JMIR Dermatology","topic":"Digital Rights Management and Security","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pemphigus; Social media; Computer science; Sociology; World Wide Web; Medicine; Dermatology","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":[0.0004245061,0.0002793744,0.0001582255,0.007247131,0.0007758182,0.001186268,0.000178322,0.0003772712,0.001983605],"category_scores_gemma":[0.001946296,0.00009861845,0.0003364652,0.003653247,0.0002449534,0.001358945,0.0007624003,0.0004061822,0.0009170006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004264375,"about_ca_system_score_gemma":0.0003551054,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004444833,"about_ca_topic_score_gemma":0.008391715,"domain_scores_codex":[0.9995945,0.0001224233,0.00004278505,0.00004890794,0.0001328698,0.00005856133],"domain_scores_gemma":[0.9978447,0.0009821791,0.0004193313,0.00009086898,0.0004898701,0.0001730413],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001330342,0.0007554693,0.5216728,0.0018339,0.0003979759,0.004111807,0.02412174,0.0008541922,0.03842069,0.004405765,0.03769393,0.3644013],"study_design_scores_gemma":[0.00001294492,0.0002003744,0.9214585,0.0003150568,0.0001420767,0.002324911,0.02388855,0.005013397,0.003615994,0.001183856,0.04178275,0.00006161367],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9693703,0.001623636,0.001548845,0.001312393,0.0001622291,0.0002304775,0.01163847,0.0001351642,0.01397836],"genre_scores_gemma":[0.9774361,0.001484835,0.004891143,0.0002240582,0.0002847029,0.000195713,0.009015638,0.00005600842,0.006411841],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007247131,"threshold_uncertainty_score":0.008837938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02805949104584584,"score_gpt":0.2914310420672541,"score_spread":0.2633715510214083,"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."}}