{"id":"W2622532295","doi":"10.1158/1078-0432.ccr-16-0115","title":"Precision Medicine in Pediatric Oncology: Translating Genomic Discoveries into Optimized Therapies","year":2017,"lang":"en","type":"review","venue":"Clinical Cancer Research","topic":"Neuroblastoma Research and Treatments","field":"Medicine","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre hospitalier de l'Université Laval; Centre hospitalier universitaire de Québec","funders":"","keywords":"Precision medicine; Epigenetics; Medicine; Personalized medicine; Cancer; Disease; Genomics; Bioinformatics; Targeted therapy; Oncology; Computational biology; Internal medicine; Biology; Pathology; Genome; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00734201,0.0005209979,0.004253422,0.001058634,0.0003808591,0.00008875151,0.0009652307,0.0007696446,0.001423393],"category_scores_gemma":[0.004793844,0.0003234518,0.0007397524,0.0007184311,0.001528568,0.0001534796,0.0004859346,0.004344259,0.0003609175],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001041436,"about_ca_system_score_gemma":0.005836855,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008994667,"about_ca_topic_score_gemma":0.0004906923,"domain_scores_codex":[0.9912837,0.002920633,0.00199994,0.001265907,0.001451826,0.001077961],"domain_scores_gemma":[0.9909366,0.006298403,0.0004941896,0.001301023,0.0003094755,0.0006602473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001503364,0.0004439783,0.0006609316,0.008252241,0.0002807179,0.0007657119,0.0001941566,4.057898e-7,0.000001010221,0.000005767604,0.00161954,0.9862722],"study_design_scores_gemma":[0.006611672,0.003504337,0.001183555,0.01380499,0.0005664711,0.00002850119,0.0000427521,0.000009816446,6.879047e-7,0.0002387019,0.9737491,0.0002594224],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0009359644,0.9882392,0.000003387493,0.002041768,0.0003742008,0.003408992,0.00003363589,0.00003600021,0.004926866],"genre_scores_gemma":[0.0004559199,0.9918404,0.0003506655,0.0000347004,0.002057152,0.001182923,0.00007535968,0.0001250291,0.003877889],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9860128,"threshold_uncertainty_score":0.9999217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.55646142280636,"score_gpt":0.6598406016677948,"score_spread":0.1033791788614348,"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."}}