{"id":"W4408658903","doi":"10.22541/au.174249381.13285606/v1","title":"Uncovering the proteogenomic landscape of head and neck squamous cell carcinoma through urine analysis","year":2025,"lang":"en","type":"preprint","venue":"","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Fundação para a Ciência e a Tecnologia; Laboratório Associado para a Química Verde; Universidade de Aveiro; Rede de Química e Tecnologia; Instituto Português de Oncologia do Porto; European Commission; European Consortium of Innovative Universities","keywords":"Head and neck; Basal cell; Head and neck squamous-cell carcinoma; Medicine; Pathology; Internal medicine; Head and neck cancer; Cancer; Surgery","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002513406,0.0002887105,0.0003035308,0.00121474,0.0002319607,0.0005010634,0.0001022935,0.0002005151,0.0005947381],"category_scores_gemma":[0.0004214881,0.00008905875,0.0002447335,0.0006897546,0.0001825916,0.0001577281,0.0002998941,0.0001711431,0.0001656792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001321092,"about_ca_system_score_gemma":0.0001742389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006441032,"about_ca_topic_score_gemma":0.0008139167,"domain_scores_codex":[0.9998562,0.00003099324,0.0000090819,0.00003531794,0.00004209525,0.00002630252],"domain_scores_gemma":[0.9998828,0.00002830921,0.00003508881,0.000009483754,0.00002710517,0.00001724112],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005754803,0.0001118985,0.1593425,0.00029754,0.0002919542,0.0006722508,0.0001876364,0.0006434314,0.7836112,0.0002763769,0.0005450295,0.05344466],"study_design_scores_gemma":[0.00001619487,0.0003551903,0.7801768,0.00003953237,0.0002195562,0.002713064,0.0004420492,0.008961654,0.2023274,0.0009689405,0.003737123,0.00004250907],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927083,0.002306184,0.003568561,0.00008498681,0.00001834822,0.00001437803,0.0008080206,0.00007006402,0.0004213074],"genre_scores_gemma":[0.9929405,0.0009394934,0.00462835,0.0000612958,0.00001649685,0.00001093437,0.000896202,0.00001850963,0.00048812],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00121474,"threshold_uncertainty_score":0.001989603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01267603996825644,"score_gpt":0.2687866472651118,"score_spread":0.2561106072968553,"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."}}