{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005133446,0.0002519744,0.0007391982,0.0002066421,0.00008363495,0.00001485454,0.0001061655,0.000100165,0.00005705873],"category_scores_gemma":[0.000131525,0.0001648922,0.0000273334,0.0003645474,0.0006564705,0.00008451172,0.0001468286,0.0004491509,0.000002283951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008833424,"about_ca_system_score_gemma":0.0001798196,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009359617,"about_ca_topic_score_gemma":0.001552235,"domain_scores_codex":[0.9982089,0.0002216593,0.0005920489,0.000467558,0.0001454917,0.0003643426],"domain_scores_gemma":[0.9990013,0.0004100631,0.0001771038,0.0002350545,0.00006176106,0.0001146825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001731513,0.0005596128,0.9442353,0.001142271,0.00005699048,0.0002936572,0.003096639,0.00004703606,0.00007601363,0.0001553822,0.0007228884,0.0478827],"study_design_scores_gemma":[0.005645984,0.0009240169,0.9825869,0.001171111,0.0001392724,0.0005757636,0.0002291132,0.001767557,0.0003956236,0.0003560937,0.006016856,0.0001916936],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9635077,0.0330563,0.00004634712,0.002047447,0.0001197191,0.0008845232,0.00002296688,0.00001381186,0.0003012402],"genre_scores_gemma":[0.9965303,0.002316961,0.00009041432,0.0001662536,0.00001949037,0.00006688599,0.00001774278,0.00001220489,0.0007797326],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.047691,"threshold_uncertainty_score":0.6724108,"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."}}