{"id":"W4407866599","doi":"10.1158/2326-6074.io2025-b108","title":"Abstract B108: nELISA high-throughput proteomics enables scalable biomarker discovery: identification of IL-1 pathway intermediates as novel CRC biomarkers","year":2025,"lang":"en","type":"article","venue":"Cancer Immunology Research","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Biomarker discovery; Proteomics; Computational biology; Biomarker; Identification (biology); Throughput; Biology; Computer science; Gene; Genetics","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":[0.0005384142,0.0004965111,0.0002968008,0.0003887152,0.0002414707,0.0005778794,0.0003435028,0.0004349459,0.004220675],"category_scores_gemma":[0.0003733092,0.0001808381,0.000317039,0.000230329,0.0002734048,0.0003817367,0.0003728056,0.0007364047,0.001423918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003696523,"about_ca_system_score_gemma":0.0004446015,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004505889,"about_ca_topic_score_gemma":0.0006535003,"domain_scores_codex":[0.9997172,0.00004126634,0.00001581878,0.00005770455,0.0001358204,0.00003217567],"domain_scores_gemma":[0.9997854,0.00004947568,0.00004972055,0.00002238646,0.00005195585,0.00004114434],"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":[0.000184683,0.00004168578,0.000461591,0.00005703561,0.000008616725,0.0000468504,0.00001097635,0.0001375314,0.9945472,0.0001548923,0.00073076,0.003618059],"study_design_scores_gemma":[0.00004381809,0.000238559,0.003284858,0.000009193684,0.00001316744,0.0002021456,0.00001139389,0.004346999,0.9852504,0.0001120479,0.006472289,0.00001518094],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9051515,0.002531743,0.07664949,0.001316603,0.000364855,0.0002738468,0.005164808,0.002377457,0.006169754],"genre_scores_gemma":[0.8924277,0.001075827,0.08844718,0.0005795971,0.00006540188,0.0002953585,0.005611498,0.0001601334,0.0113373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004220675,"threshold_uncertainty_score":0.01411951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0316114799888591,"score_gpt":0.370225012542262,"score_spread":0.3386135325534029,"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."}}