{"id":"W3035120337","doi":"10.1016/j.cancergen.2020.04.017","title":"13. Bioinformatics and interpretation for clinical reporting of an integrated whole genome and transcriptome assay","year":2020,"lang":"en","type":"article","venue":"Cancer Genetics","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Institute for Cancer Research","funders":"","keywords":"Transcriptome; Genome; Computational biology; Whole genome sequencing; Genomics; Bioinformatics; Personal genomics; Profiling (computer programming); Biology; Gene; Genetics; Computer science; Gene expression","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00498118,0.001805354,0.001181574,0.003217301,0.001114334,0.003260569,0.001807496,0.002346332,0.06839039],"category_scores_gemma":[0.01365003,0.001342383,0.0009814795,0.001366198,0.0006462131,0.00127042,0.001728145,0.001546677,0.05741052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001606058,"about_ca_system_score_gemma":0.002497933,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004812305,"about_ca_topic_score_gemma":0.006266415,"domain_scores_codex":[0.99751,0.0005098891,0.0004405251,0.0004860255,0.0007321797,0.0003213752],"domain_scores_gemma":[0.9876794,0.004975,0.00111802,0.002062359,0.003483313,0.0006818025],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003457893,0.0005310933,0.01806584,0.001244613,0.0002359154,0.001467382,0.0006398826,0.003124095,0.05523286,0.005298544,0.6951948,0.2155071],"study_design_scores_gemma":[0.001312393,0.0004645236,0.0534166,0.0009674448,0.0002742873,0.001421667,0.0004063496,0.08477584,0.2912125,0.0202644,0.5448894,0.0005945828],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"methods","genre_scores_codex":[0.0110778,0.000308071,0.2811876,0.003453382,0.0005267955,0.002125804,0.1141546,0.5678649,0.01930111],"genre_scores_gemma":[0.1052297,0.0005522951,0.5907176,0.008580213,0.0007320434,0.006924402,0.1975132,0.04750726,0.0422433],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.06839039,"threshold_uncertainty_score":0.2287887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0407971360093999,"score_gpt":0.3382503439421368,"score_spread":0.2974532079327369,"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."}}