{"id":"W3128220657","doi":"10.1002/ccr3.3804","title":"NTRK2 Fusion driven pediatric glioblastoma: Identification of oncogenic Drivers via integrative Genome and transcriptome profiling","year":2021,"lang":"en","type":"article","venue":"Clinical Case Reports","topic":"Glioma Diagnosis and Treatment","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Children's & Women's Health Centre of British Columbia; BC Children's Hospital; BC Cancer Agency; Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"BC Cancer Agency","keywords":"Glioblastoma; Medicine; Transcriptome; Genome; Profiling (computer programming); Fusion gene; Gene expression profiling; Computational biology; Bioinformatics; Cancer research; Gene; Genetics; Biology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005088951,0.0001703993,0.0005594645,0.0001229085,0.00007710432,0.00001612911,0.00002001407,0.0001640341,0.0000566982],"category_scores_gemma":[0.0005440337,0.0001370012,0.0003067532,0.0003507395,0.000111467,0.00007559516,0.00004554087,0.0002111859,0.00000658454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006680073,"about_ca_system_score_gemma":0.0002051555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001641934,"about_ca_topic_score_gemma":0.00001906367,"domain_scores_codex":[0.9975674,0.0001070156,0.001328133,0.0005623961,0.0002629375,0.0001721279],"domain_scores_gemma":[0.9981872,0.0002134627,0.0005286831,0.0004178942,0.0004070136,0.000245745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002036752,0.002488836,0.4971206,0.0003074476,0.0003851358,0.342313,0.0006458069,0.00001284419,0.1479352,0.00004876983,0.00008040301,0.008458284],"study_design_scores_gemma":[0.007360077,0.003318572,0.5514767,0.0002854854,0.00584852,0.2374876,0.002118396,0.001051334,0.1888431,0.0006009197,0.0008845581,0.0007246905],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972064,0.00140388,0.0002031687,0.0002255128,0.0003465805,0.0004917722,0.00001495538,0.00003340219,0.00007436486],"genre_scores_gemma":[0.9979746,0.0008798643,0.000744649,0.00004710269,0.000167142,0.00003151365,0.0000650945,0.0000189579,0.00007111843],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1048253,"threshold_uncertainty_score":0.5586749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02586925727397052,"score_gpt":0.3340277330678455,"score_spread":0.308158475793875,"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."}}