{"id":"W4411091795","doi":"10.3390/curroncol32060333","title":"Germline TP53 p.R337H and XAF1 p.E134* Variants: Prevalence in Paraguay and Comparison with Rates in Brazilian State of Paraná and Previous Findings at the Paraguayan–Brazilian Border","year":2025,"lang":"en","type":"article","venue":"Current Oncology","topic":"Adrenal and Paraganglionic Tumors","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Consejo Nacional de Ciencia y Tecnología; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Universidad Nacional de Asunción","keywords":"Germline; Medicine; State (computer science); Demography; Genetics; Environmental health; Biology; Gene; Sociology; Computer science","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":[0.0003679954,0.0002835761,0.0002517908,0.001301066,0.0003984808,0.0005059625,0.0004268735,0.0002763033,0.0009555762],"category_scores_gemma":[0.001236744,0.0003068024,0.0003376849,0.001108755,0.0006315946,0.0003263486,0.0006269878,0.0002758148,0.0001103249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000774248,"about_ca_system_score_gemma":0.0005023214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08387417,"about_ca_topic_score_gemma":0.1002198,"domain_scores_codex":[0.9996929,0.00005233139,0.00003289802,0.0001035989,0.00006081099,0.00005751351],"domain_scores_gemma":[0.9992833,0.00008068883,0.0003766147,0.00005872241,0.0001071913,0.00009342793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002838281,0.00001541346,0.9960117,0.00004186602,0.00003480185,0.0001972682,0.0009012381,0.00002535373,0.0008103288,0.0001231471,0.00005877348,0.001751709],"study_design_scores_gemma":[0.000003438275,0.00003434004,0.9973705,0.00002840061,0.0000265967,0.000772638,0.001142232,0.00009665987,0.00008152278,0.00003896022,0.0004004003,0.0000042791],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983451,0.0003495917,0.0001038908,0.00005259202,0.000002985096,0.00001680335,0.0002943624,0.000004674418,0.0008300039],"genre_scores_gemma":[0.99933,0.0002832313,0.0001379084,0.00001601933,0.000002157968,0.00001162482,0.0001505117,0.000002432881,0.00006606666],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08387417,"threshold_uncertainty_score":0.1667719,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02743551614127247,"score_gpt":0.3890922703488072,"score_spread":0.3616567542075347,"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."}}