{"id":"W2208730418","doi":"10.1186/s13104-015-1803-7","title":"A cancer cell-line titration series for evaluating somatic classification","year":2015,"lang":"en","type":"article","venue":"BMC Research Notes","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research","funders":"","keywords":"Somatic cell; Computational biology; Exome; Genome; Biology; Genetics; DNA sequencing; Exome sequencing; Indel; Bioinformatics; Computer science; DNA; Single-nucleotide polymorphism; Mutation; Genotype; Gene","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":[0.0009925127,0.00006889895,0.00007218107,0.00002758471,0.0001068864,0.00006222281,0.0001147489,0.00007262859,0.0000110083],"category_scores_gemma":[0.002328173,0.00006583563,0.00003548923,0.0000708622,0.00005388553,0.000007354565,0.00005890023,0.00004982322,0.000008613182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007119867,"about_ca_system_score_gemma":0.0006932302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002519037,"about_ca_topic_score_gemma":0.001914497,"domain_scores_codex":[0.9991099,0.00008203131,0.0001455248,0.0002168716,0.0002303743,0.0002153066],"domain_scores_gemma":[0.998866,0.0001670464,0.0000475537,0.0002279307,0.0006046245,0.00008687589],"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":[0.0002985438,0.00006948962,0.004019673,0.000116461,0.00001392115,1.705009e-7,0.0001898596,0.001399909,0.9829198,0.0006244783,0.005619482,0.004728233],"study_design_scores_gemma":[0.001750092,0.001919447,0.003580107,0.00004376792,0.00002761069,0.000002418419,0.001180765,0.03947102,0.9288546,0.004822973,0.01805743,0.0002897682],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9737993,0.003256188,0.02031656,0.0006998651,0.0001974127,0.0007715034,0.00007165744,0.00001128185,0.0008762115],"genre_scores_gemma":[0.9881725,0.0004418453,0.009437941,0.00004223239,0.0006008967,0.00046012,0.0002021364,0.00001918094,0.0006231189],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05406518,"threshold_uncertainty_score":0.2787209,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3967892056663921,"score_gpt":0.4926825396069579,"score_spread":0.09589333394056582,"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."}}