{"id":"W2962028921","doi":"10.1093/bioinformatics/btz355","title":"Collaborative intra-tumor heterogeneity detection","year":2019,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency; Simon Fraser University","funders":"","keywords":"Computer science; Inference; Phylogenetic tree; Deconvolution; Source code; Process (computing); Data mining; Computational biology; Machine learning; Artificial intelligence; Biology; Algorithm; Genetics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003167739,0.001379907,0.002405248,0.002329268,0.0008315964,0.001611198,0.003122259,0.001952344,0.001215022],"category_scores_gemma":[0.007328323,0.0007128413,0.001431711,0.001737532,0.0007825904,0.001313562,0.002326644,0.00128926,0.0008792857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007462281,"about_ca_system_score_gemma":0.001180922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00546622,"about_ca_topic_score_gemma":0.005893758,"domain_scores_codex":[0.9967758,0.0006215404,0.0001375512,0.001440195,0.0007024889,0.0003223427],"domain_scores_gemma":[0.9945366,0.002947109,0.0006051318,0.0009237706,0.0006165878,0.0003707488],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001236617,0.0003721431,0.0405851,0.0005955007,0.0009183019,0.002118727,0.0006154707,0.3713136,0.0364132,0.00519262,0.0198014,0.5208373],"study_design_scores_gemma":[0.00004338129,0.0001076146,0.004570236,0.00002294902,0.0001435855,0.00101186,0.00009902463,0.9696701,0.01131615,0.008951764,0.004018829,0.00004456045],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09111304,0.002454398,0.8989091,0.0007573547,0.0001239393,0.0001846974,0.001350553,0.002777545,0.002329398],"genre_scores_gemma":[0.7849638,0.0006503361,0.2044818,0.0004806663,0.0003562804,0.0001754151,0.004164267,0.0002931955,0.004434356],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00546622,"threshold_uncertainty_score":0.01675278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004623206389557855,"score_gpt":0.2230465216424029,"score_spread":0.218423315252845,"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."}}