{"id":"W4388845885","doi":"10.1038/s41467-023-42701-9","title":"Targetable lesions and proteomes predict therapy sensitivity through disease evolution in pediatric acute lymphoblastic leukemia","year":2023,"lang":"en","type":"article","venue":"Nature Communications","topic":"PARP inhibition in cancer therapy","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia Hospital; BC Children's Hospital; University of British Columbia","funders":"CIHR Skin Research Training Centre; Canadian Institutes of Health Research; BC Children's Hospital; Michael Smith Health Research BC; Canada Research Chairs; Government of Canada; Children's Hospital Foundation","keywords":"Proteome; Disease; Genome; Medicine; Computational biology; Transcriptome; Lymphoblastic Leukemia; Bioinformatics; Oncology; Biology; Leukemia; Internal medicine; Genetics; Gene; Gene expression","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":[0.000325291,0.0002085513,0.0001866063,0.0006740042,0.0001306027,0.0006398512,0.0001341465,0.000222581,0.0006330965],"category_scores_gemma":[0.0007567191,0.0001403738,0.0001282574,0.000599551,0.0001992084,0.0003306977,0.0002991103,0.0002919774,0.0001985614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001809632,"about_ca_system_score_gemma":0.0001027086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006203529,"about_ca_topic_score_gemma":0.0007752868,"domain_scores_codex":[0.99985,0.00002745837,0.00001299564,0.00004247336,0.00004529901,0.00002178156],"domain_scores_gemma":[0.9997224,0.00006689133,0.0001239014,0.00002665548,0.00003140376,0.00002861123],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008812345,0.00005141583,0.6194274,0.000101813,0.0001469164,0.000590934,0.0002070071,0.002148687,0.3419355,0.0002117543,0.0006132049,0.03368429],"study_design_scores_gemma":[0.000005738879,0.0001181443,0.9344203,0.000008272565,0.00007067418,0.002003642,0.0001492408,0.00310085,0.05819074,0.0002875945,0.001635221,0.000009502377],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965617,0.0009808773,0.00121424,0.00005182434,0.000003720575,0.00000654274,0.000712041,0.00004676004,0.0004223332],"genre_scores_gemma":[0.9972895,0.0004629273,0.001247956,0.00003466416,0.000005436798,0.000005871756,0.0007612503,0.0000136213,0.000178852],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006740042,"threshold_uncertainty_score":0.002117872,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02582398150362697,"score_gpt":0.325753606787501,"score_spread":0.2999296252838741,"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."}}