{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00195395,0.000785065,0.001285654,0.002345231,0.0004120835,0.001259028,0.001134129,0.001993979,0.002439128],"category_scores_gemma":[0.002343107,0.0003012309,0.0006419237,0.002453713,0.0009441008,0.002265543,0.0009064837,0.002714637,0.001590222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001217587,"about_ca_system_score_gemma":0.001819028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002107535,"about_ca_topic_score_gemma":0.003578753,"domain_scores_codex":[0.9995744,0.0001194113,0.00004695206,0.00006555249,0.0001535045,0.00004020399],"domain_scores_gemma":[0.9988546,0.0007294696,0.00008773831,0.00003037822,0.0002209838,0.0000767186],"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":[0.00004794022,0.00003087641,0.0002955181,0.01245445,0.000101607,0.000180588,0.0001120114,0.0005267847,0.001333839,0.008840197,0.03293156,0.9431447],"study_design_scores_gemma":[0.000007635679,0.00004422188,0.0007090754,0.004379975,0.00008368605,0.0009294922,0.0001047304,0.0001581657,0.0005415192,0.006358284,0.9866564,0.00002686181],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00006934151,0.9976859,0.0003252335,0.0009579043,0.0002479142,0.000004174977,0.00001510777,0.00000785481,0.0006865915],"genre_scores_gemma":[0.0005025928,0.9980945,0.0004141523,0.0004812099,0.0001451906,0.000006251864,0.00002399848,0.000002094991,0.0003299995],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002439128,"threshold_uncertainty_score":0.0103336,"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."}}