{"id":"W4308653809","doi":"10.1158/0008-5472.can-22-1433","title":"Immunotherapeutic Targeting and PET Imaging of DLL3 in Small-Cell Neuroendocrine Prostate Cancer","year":2022,"lang":"en","type":"article","venue":"Cancer Research","topic":"Lung Cancer Research Studies","field":"Medicine","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; BC Cancer Agency","funders":"National Institute of General Medical Sciences; National Cancer Institute; Canadian Institutes of Health Research; Genentech; National Institutes of Health; University of California, San Francisco; Scheme for Promotion of Academic and Research Collaboration; Astellas Pharma; Clovis Oncology; U.S. Department of Defense; Sanofi; Celgene; Prostate Cancer Foundation; AstraZeneca; Amgen; Pfizer; Advanced Accelerator Applications","keywords":"Prostate cancer; Medicine; Immunotherapy; Cancer; Cancer research; T cell; Immunology; Internal medicine; Immune system","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001133692,0.0001548031,0.000368917,0.0005144494,0.0003070095,0.00002632015,0.0002412684,0.000007365076,0.0007390826],"category_scores_gemma":[0.0001220135,0.0001442231,0.00004990874,0.001035342,0.0003604168,0.00007197873,0.0008121859,0.001156945,0.00000216632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008207131,"about_ca_system_score_gemma":0.0008518288,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008964457,"about_ca_topic_score_gemma":0.0004108067,"domain_scores_codex":[0.9970871,0.0003754419,0.0003340894,0.0004765475,0.0008516815,0.0008750911],"domain_scores_gemma":[0.9989799,0.0002207814,0.00007047477,0.0003045541,0.0002976004,0.0001267497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00233104,0.0003149328,0.5570263,0.002206157,0.0001439518,0.001448585,0.004728756,0.0002940209,0.4030983,0.00006200209,0.004548057,0.02379786],"study_design_scores_gemma":[0.04925468,0.004837661,0.3461784,0.003065884,0.0003208759,0.0008961374,0.04700716,0.009309249,0.3025737,0.001887906,0.2324765,0.002191742],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9342518,0.05739909,0.00000106453,0.006366221,0.000111973,0.001112559,0.00005978356,0.00002452751,0.0006729119],"genre_scores_gemma":[0.9823396,0.01296805,0.0000505906,0.0002466766,0.00008631324,0.001684611,0.000007534377,0.00005572492,0.002560885],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2279285,"threshold_uncertainty_score":0.9976349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05384630294626189,"score_gpt":0.4139175327944468,"score_spread":0.3600712298481848,"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."}}