{"id":"W4386457031","doi":"10.1097/01.cot.0000978392.43371.00","title":"Plasma miR371 as Reliable Biomarker for Testicular Cancer Surveillance","year":2023,"lang":"en","type":"article","venue":"Oncology Times","topic":"Testicular diseases and treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Biomarker; Testicular cancer; Orchiectomy; Internal medicine; Stage (stratigraphy); Oncology; Cancer","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001080524,0.0004262489,0.0006744887,0.001271891,0.0003821008,0.001382868,0.0003330085,0.000489668,0.001361701],"category_scores_gemma":[0.002322234,0.0002329845,0.0003507204,0.001267516,0.0003009757,0.000430433,0.0003369652,0.0005454689,0.0005987641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009051503,"about_ca_system_score_gemma":0.0007853149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003050611,"about_ca_topic_score_gemma":0.004196322,"domain_scores_codex":[0.9992866,0.00019871,0.00005743576,0.000130252,0.0002558832,0.0000711208],"domain_scores_gemma":[0.9991308,0.0002366766,0.0002691541,0.00005408947,0.0002028718,0.0001064438],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001423333,0.0001036534,0.8964348,0.000306375,0.0002457856,0.0005187668,0.0002699751,0.000835191,0.03392633,0.0002543125,0.00150269,0.06417871],"study_design_scores_gemma":[0.00006120567,0.0008802676,0.9362777,0.0001658202,0.0003517725,0.00416064,0.0004212096,0.009826277,0.03704362,0.0006020952,0.01015694,0.00005240093],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9684632,0.0209944,0.004642278,0.0005335243,0.0001123835,0.00009588914,0.00135226,0.0002610467,0.003544971],"genre_scores_gemma":[0.9946448,0.001332767,0.002421056,0.00009503717,0.00004401326,0.0000309182,0.0006937447,0.00001652573,0.0007211175],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003050611,"threshold_uncertainty_score":0.006567419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02904009694599048,"score_gpt":0.3573841158715449,"score_spread":0.3283440189255544,"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."}}