{"id":"W2619065478","doi":"10.1038/nmeth.4303","title":"E-scape: interactive visualization of single-cell phylogenetics and cancer evolution","year":2017,"lang":"en","type":"letter","venue":"Nature Methods","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":54,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; BC Cancer Agency","funders":"BC Cancer Foundation","keywords":"Visualization; Scape; Phylogenetics; Biology; Computational biology; Computer science; Evolutionary biology; Genetics; Data mining; Gene; Botany","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","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.0002194793,0.0002579019,0.0003154009,0.00008367652,0.00006786184,0.0000409865,0.0002504902,0.001867409,0.00001136646],"category_scores_gemma":[0.0004427393,0.0002598449,0.0001090083,0.00004621932,0.0001196316,0.000002890334,0.0001955092,0.0007099406,4.259596e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006403239,"about_ca_system_score_gemma":0.0001624604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004643795,"about_ca_topic_score_gemma":0.00002146414,"domain_scores_codex":[0.9987915,0.0001850562,0.0002277175,0.0004637545,0.0001349682,0.0001970311],"domain_scores_gemma":[0.9985623,0.0001072041,0.0004916445,0.0005097513,0.0002919222,0.00003713895],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005987308,0.00004020414,0.0003199922,0.0002388456,0.0001238415,0.000005884031,0.00004492966,0.00002276372,0.6723393,0.00002313793,0.3091041,0.01767719],"study_design_scores_gemma":[0.0002546952,0.0001576201,0.0002503115,0.00005592953,0.0001264103,0.000005705222,0.000005728891,0.00004745804,0.3059863,0.0001841071,0.692696,0.000229629],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.05649704,0.4923408,0.3390473,0.07292826,0.01819363,0.002810035,0.003116572,0.00006479534,0.01500158],"genre_scores_gemma":[0.3464011,0.03764554,0.2820262,0.2752343,0.04008585,0.0003153589,0.005739664,0.0007903369,0.01176175],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4546953,"threshold_uncertainty_score":0.9999854,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01493694212429439,"score_gpt":0.359842548116577,"score_spread":0.3449056059922825,"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."}}