{"id":"W4383313483","doi":"10.3389/fonc.2023.1208244","title":"Molecular profiling of solid tumors by next-generation sequencing: an experience from a clinical laboratory","year":2023,"lang":"en","type":"article","venue":"Frontiers in Oncology","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Provincial Laboratory of Public Health; Western University; London Health Sciences Centre","funders":"","keywords":"Profiling (computer programming); DNA sequencing; Computational biology; Solid tumor; Medicine; Medical physics; Computer science; Biology; Internal medicine; Genetics; DNA; Cancer; Operating system","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":[],"consensus_categories":[],"category_scores_codex":[0.0003246226,0.00011382,0.000279791,0.00006528754,0.0000296166,0.00000913624,0.0002065774,0.000260543,0.000004476526],"category_scores_gemma":[0.0003206626,0.0001300911,0.00005246716,0.0001777045,0.0001530139,0.000007159422,0.0000880368,0.0001162603,0.000002268727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008790852,"about_ca_system_score_gemma":0.0005001169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008394672,"about_ca_topic_score_gemma":0.00007758114,"domain_scores_codex":[0.998691,0.0001589362,0.0004360499,0.0004039088,0.00008452986,0.0002256053],"domain_scores_gemma":[0.999361,0.00002876137,0.000147721,0.0002979604,0.0000751546,0.00008940767],"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":[0.00006807206,0.00007030043,0.02419372,0.000004357378,0.00002224199,0.00002822574,0.000242789,0.0008888114,0.9565181,0.00002413314,0.01443134,0.003507921],"study_design_scores_gemma":[0.000965265,0.001007502,0.001231307,0.0000108136,0.00001717288,0.000001620545,0.001957008,0.01401493,0.9606919,0.0002448096,0.01959532,0.0002623104],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914833,0.001041448,0.005862012,0.00007193902,0.001108708,0.0001647868,0.0001830764,0.00001245984,0.00007223336],"genre_scores_gemma":[0.9870434,0.0008099426,0.01052626,0.0005272928,0.0003084609,0.00005667694,0.0006887863,0.00002264155,0.00001648741],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02296241,"threshold_uncertainty_score":0.5304962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04950415293933462,"score_gpt":0.346763811013341,"score_spread":0.2972596580740063,"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."}}