{"id":"W4402266434","doi":"10.1158/1538-7445.pediatric24-pr004","title":"Abstract PR004: Next generation pediatric precision oncology: Functional profiling of patient-derived viable tumor material to link genotype and phenotype","year":2024,"lang":"en","type":"article","venue":"Cancer Research","topic":"Sarcoma Diagnosis and Treatment","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Precision oncology; Medicine; Genotype; Pediatric oncology; Phenotype; Oncology; Internal medicine; Profiling (computer programming); Computational biology; Bioinformatics; Cancer; Biology; Genetics; Computer science; Gene","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004785385,0.0003762727,0.0003827644,0.0006853509,0.0002030317,0.0004973452,0.0003285273,0.0002903521,0.002777407],"category_scores_gemma":[0.0004748889,0.0001354373,0.0003296564,0.000589769,0.0002066525,0.0001598141,0.000368981,0.0003985891,0.0009940313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000288008,"about_ca_system_score_gemma":0.0003564158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005232153,"about_ca_topic_score_gemma":0.000706134,"domain_scores_codex":[0.9996916,0.00004558134,0.00001583119,0.00008808509,0.0001194577,0.00003952874],"domain_scores_gemma":[0.9997571,0.00007571041,0.00004500254,0.00003827724,0.00004273793,0.00004105248],"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":[0.0008385862,0.00008660284,0.0357954,0.0002250512,0.00008234978,0.000284237,0.00009177998,0.001906601,0.9172733,0.0003067019,0.002178801,0.04093068],"study_design_scores_gemma":[0.0000681645,0.001669468,0.2212601,0.00004246379,0.0002441936,0.00316739,0.0001939409,0.01164872,0.7343036,0.0008237077,0.0265317,0.00004653547],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9333025,0.001798469,0.03408878,0.000392812,0.00003589358,0.0002273574,0.02526182,0.001095784,0.003796506],"genre_scores_gemma":[0.9076142,0.001398837,0.04872399,0.0002330787,0.00003210367,0.0003160617,0.03746115,0.0002715031,0.003948954],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002777407,"threshold_uncertainty_score":0.009291291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1298236690505636,"score_gpt":0.3987203447480792,"score_spread":0.2688966756975156,"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."}}