{"id":"W4390757470","doi":"10.1158/1538-7445.dnarepair24-ia003","title":"Abstract IA003: Molecular and imaging biomarkers of PARP inhibitors for small cell lung cancer","year":2024,"lang":"en","type":"article","venue":"Cancer Research","topic":"Lung Cancer Research Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre","funders":"","keywords":"Lung cancer; Medicine; Context (archaeology); PARP inhibitor; Cancer; Cancer research; Liquid biopsy; Positron emission tomography; Biomarker; Oncology; Poly ADP ribose polymerase; Bioinformatics; Pathology; Internal medicine; Nuclear medicine; DNA; Biology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001234391,0.0001896018,0.0003449993,0.0005057359,0.0001427373,0.00008512328,0.0001667915,0.00007116498,0.0001853025],"category_scores_gemma":[0.0002119174,0.0001576373,0.0001314453,0.0007012346,0.0005148272,0.0001018877,0.0002113728,0.0005146466,0.000003725488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006611539,"about_ca_system_score_gemma":0.001339174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002862808,"about_ca_topic_score_gemma":0.0001804666,"domain_scores_codex":[0.9974685,0.00006209285,0.000301373,0.0005865135,0.000784924,0.000796635],"domain_scores_gemma":[0.9983686,0.0004266048,0.00003765942,0.0003044708,0.0005915627,0.0002710596],"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":[0.0007385455,0.00008416962,0.03487748,0.01860738,0.0008855522,0.0002797969,0.001347525,0.00001946745,0.7954581,0.0001848253,0.09746369,0.0500535],"study_design_scores_gemma":[0.003489387,0.0003532089,0.01307658,0.006524201,0.0003418942,0.0000139887,0.001532168,0.002608456,0.913618,0.0004370615,0.05750102,0.0005039909],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7810196,0.2080769,0.00009183548,0.005992132,0.0003429956,0.001842126,0.0001623305,0.00006488388,0.002407145],"genre_scores_gemma":[0.9905693,0.006467812,0.0002060826,0.0000734437,0.0003536653,0.001288507,0.000009785444,0.00007611686,0.00095531],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2095496,"threshold_uncertainty_score":0.6428264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04924374847328876,"score_gpt":0.4434771862253096,"score_spread":0.3942334377520209,"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."}}