{"id":"W1759847609","doi":"10.3390/cancers7030869","title":"Next-Generation Sequencing Approaches in Cancer: Where Have They Brought Us and Where Will They Take Us?","year":2015,"lang":"en","type":"review","venue":"Cancers","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Canada's Michael Smith Genome Sciences Centre; Genome British Columbia; BC Cancer Agency","funders":"BC Cancer Agency; BC Cancer Foundation; University of British Columbia; Genome British Columbia; Canadian Institutes of Health Research; Leukemia and Lymphoma Society; Genome Canada; Cancer Research Society; Canada's Michael Smith Genome Sciences Centre; Leukemia and Lymphoma Society of Canada","keywords":"Cancer; Computer science; Data science; Computational biology; Medicine; Biology; Internal medicine","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002436031,0.0005019658,0.0008720432,0.00007761388,0.00007872926,0.0001253086,0.0002851993,0.0005538787,0.00001395019],"category_scores_gemma":[0.00003875161,0.0004574123,0.0001811809,0.00008186254,0.00008517154,0.00001460355,0.0001526576,0.0002957625,0.000002783127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002107023,"about_ca_system_score_gemma":0.003364852,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.007104812,"about_ca_topic_score_gemma":0.09426864,"domain_scores_codex":[0.9980689,0.0001101642,0.0004609763,0.0007944249,0.0001588816,0.0004066946],"domain_scores_gemma":[0.9988981,0.00002269168,0.0003176131,0.0005015885,0.00008723223,0.000172787],"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":[0.00003877193,0.00001880581,0.0006751164,0.005384507,0.0003368467,0.000024514,0.0004622754,0.006421349,0.000645918,0.00009593918,0.01266452,0.9732314],"study_design_scores_gemma":[0.000361914,0.00008836584,0.00000425729,0.001625616,0.0002197884,0.00002300079,0.0001382261,0.0003511658,0.00006383176,0.00002856702,0.9965336,0.0005617164],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.004462508,0.9929228,0.00002209688,0.00005351821,0.0005241625,0.0007013816,0.0004014804,0.0000100502,0.0009020418],"genre_scores_gemma":[0.002524895,0.994271,0.0001563306,0.000123916,0.001481327,0.0003598258,0.0005329137,0.00009719296,0.0004525551],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.983869,"threshold_uncertainty_score":0.9997877,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1216246394770041,"score_gpt":0.3082790490745708,"score_spread":0.1866544095975667,"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."}}