{"id":"W2977291034","doi":"","title":"Subpoplar: reconstructing cancer phylogenies by ordering mutation pairs","year":2018,"lang":"en","type":"article","venue":"Research in Computational Molecular Biology","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Mutation; Computational biology; Evolutionary biology; Computer science; Genetics; Biology; 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":[0.0005460645,0.0001248608,0.0001299235,0.000167176,0.0001452557,0.00003469765,0.0001972707,0.0001565127,0.00003404268],"category_scores_gemma":[0.0002856502,0.0001387384,0.00004510976,0.0002883456,0.0004064871,0.000003726205,0.0001784609,0.0001751234,0.00001433485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007414053,"about_ca_system_score_gemma":0.000283734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000453055,"about_ca_topic_score_gemma":0.0003430579,"domain_scores_codex":[0.9984807,0.0002365589,0.0002409004,0.0004552399,0.0001611274,0.0004254528],"domain_scores_gemma":[0.9991756,0.0001443017,0.0000588966,0.0001644759,0.0003781439,0.00007859124],"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":[0.0001680133,0.0000856802,0.02756901,0.00003109361,0.0001011662,0.00002494316,0.0001002264,0.007681369,0.9211073,0.005936936,0.002879874,0.0343144],"study_design_scores_gemma":[0.004724049,0.003252784,0.007837359,0.000177976,0.0000262313,0.0002310342,0.000715734,0.02898728,0.7362067,0.1536551,0.06259007,0.001595747],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9683268,0.001960795,0.02778819,0.0007718649,0.0002266625,0.000216821,0.0001169582,0.000009575638,0.0005823164],"genre_scores_gemma":[0.9942498,0.0001770563,0.00444443,0.000257426,0.0002871152,0.00007350547,0.0004659308,0.00002286013,0.00002190631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1849006,"threshold_uncertainty_score":0.5657587,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03600871711862112,"score_gpt":0.3880055430303447,"score_spread":0.3519968259117236,"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."}}