{"id":"W4391359379","doi":"10.1186/s12014-024-09452-1","title":"Recent developments in mass-spectrometry-based targeted proteomics of clinical cancer biomarkers","year":2024,"lang":"en","type":"review","venue":"Clinical Proteomics","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; University of Toronto; Hospital for Sick Children; Princess Margaret Cancer Centre; University Health Network","funders":"Canadian Institutes of Health Research; Canada Research Chairs; Ontario Ministry of Health and Long-Term Care","keywords":"Proteomics; Biomarker discovery; Biomarker; Cancer biomarkers; Quantitative proteomics; Cancer; Medicine; Computational biology; Workflow; Bioinformatics; Computer science; Biology; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001654673,0.001305851,0.001384777,0.002909195,0.0002729761,0.001199504,0.001035169,0.001365373,0.002281063],"category_scores_gemma":[0.001430053,0.0005041853,0.0007073689,0.003218582,0.0006685962,0.001916162,0.001057942,0.002392754,0.002282458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008036807,"about_ca_system_score_gemma":0.001130452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007390266,"about_ca_topic_score_gemma":0.0008355125,"domain_scores_codex":[0.9995238,0.00009180308,0.00004965074,0.00009486277,0.0001943736,0.00004554192],"domain_scores_gemma":[0.9991148,0.0004735414,0.00009472219,0.00002729354,0.000231148,0.00005851994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001058089,0.000134792,0.0002636986,0.02598972,0.0001473576,0.000293263,0.00007844051,0.0009128632,0.006530155,0.008610328,0.02373084,0.9332026],"study_design_scores_gemma":[0.00002170015,0.0001810573,0.0006842015,0.001982744,0.0001154055,0.00100094,0.00004355062,0.0003231502,0.002358848,0.003444735,0.9898053,0.00003832611],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001542089,0.9975038,0.0006624578,0.0002720385,0.0001931984,0.000009364966,0.00001766855,0.00001398406,0.001173281],"genre_scores_gemma":[0.0008272777,0.9975084,0.0006443386,0.0002810658,0.0002018239,0.00001279997,0.00003409653,0.000002974402,0.0004870813],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002909195,"threshold_uncertainty_score":0.008750856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.147839258695487,"score_gpt":0.48470526227128,"score_spread":0.336866003575793,"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."}}