{"id":"W4389227701","doi":"10.1158/2326-6074.tumimm23-a029","title":"Abstract A029: Treatment-Specific Immune Phenotypes Identified by nELISA High-Throughput Proteomics Reveal Actionable Insights for Drug Discovery","year":2023,"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":"Proteomics; Immune system; Biology; Cytokine; Phenotype; Computational biology; Proteases; Immunotherapy; Tumor microenvironment; Chemokine; Peripheral blood mononuclear cell; Drug discovery; Immunology; Bioinformatics; Gene; Genetics; In vitro; Enzyme; Biochemistry","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002673782,0.0001927384,0.0002176974,0.0001099087,0.0005499327,0.00007883265,0.0003330521,0.0002290161,0.00001615863],"category_scores_gemma":[0.00004239769,0.0001743758,0.0001045987,0.0003430507,0.0003777286,0.00002528671,0.0001917883,0.0002265071,0.00004057376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001919526,"about_ca_system_score_gemma":0.0001914412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003777018,"about_ca_topic_score_gemma":0.00006062158,"domain_scores_codex":[0.998326,0.00007087801,0.0002710218,0.0006246056,0.0001440918,0.0005633744],"domain_scores_gemma":[0.9988748,0.00007777358,0.00009460005,0.000655025,0.0002515682,0.00004624397],"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":[0.0003094008,0.00008778246,0.00002202517,0.00001652257,0.0001139654,0.00000152001,0.00004731531,0.00002350935,0.9439284,0.0007492968,0.0497852,0.004915108],"study_design_scores_gemma":[0.0005748596,0.0001525527,0.0008789005,0.00001788785,0.000007099104,0.00000194754,0.000138663,0.000007595212,0.7484945,0.002804248,0.2467617,0.0001600635],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.986182,0.007089025,0.002381008,0.001883814,0.0003191707,0.001495161,0.0003458309,0.000114105,0.000189909],"genre_scores_gemma":[0.9499966,0.01927575,0.001782586,0.00004515137,0.0004490333,0.002407751,0.001974223,0.00007026178,0.02399865],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1969765,"threshold_uncertainty_score":0.7110837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04862144729291532,"score_gpt":0.3739854669666774,"score_spread":0.3253640196737621,"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."}}