{"id":"W4403011519","doi":"10.1038/s41467-024-52544-7","title":"Inferring replication timing and proliferation dynamics from single-cell DNA sequencing data","year":2024,"lang":"en","type":"article","venue":"Nature Communications","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Marie-Josée and Henry R. Kravis Center for Molecular Oncology; National Cancer Institute; National Institutes of Health; U.S. Department of Health and Human Services; Cancer Research UK; Cycle for Survival; Ovarian Cancer Research Alliance; National Human Genome Research Institute; Memorial Sloan-Kettering Cancer Center","keywords":"DNA replication; Computational biology; DNA sequencing; Replication (statistics); DNA; Computer science; Biology; Genetics; Virology","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":[0.001132811,0.0004484798,0.0003709373,0.0008110385,0.0002773344,0.0007481591,0.0005530216,0.0007366356,0.0003655381],"category_scores_gemma":[0.005398347,0.0004695207,0.0006540265,0.0006769116,0.0004230024,0.0007215807,0.0004655926,0.0006688744,0.0001682908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006362718,"about_ca_system_score_gemma":0.0007177102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004669921,"about_ca_topic_score_gemma":0.007904318,"domain_scores_codex":[0.9996585,0.00008743088,0.00001845067,0.0001483936,0.00006782441,0.00001938189],"domain_scores_gemma":[0.9978371,0.001536281,0.0002992942,0.000173574,0.0001017327,0.00005209982],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002220097,0.00005296886,0.04219412,0.0001994341,0.0002179923,0.0001789627,0.0001316105,0.8349162,0.08577349,0.004230082,0.0003826441,0.03150051],"study_design_scores_gemma":[0.000005970635,0.00002598883,0.007101671,0.000006758117,0.00002226631,0.00008110834,0.00001434654,0.9731741,0.01355937,0.005447944,0.0005424854,0.00001793685],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5233957,0.0005373746,0.472235,0.0001798162,0.00001899293,0.00003534008,0.001698816,0.001231139,0.0006678717],"genre_scores_gemma":[0.9065154,0.0003103351,0.09015635,0.00006794155,0.0000176958,0.0000550952,0.002274864,0.0001302432,0.0004720628],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004669921,"threshold_uncertainty_score":0.00928551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04551303457594872,"score_gpt":0.3118867889080939,"score_spread":0.2663737543321452,"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."}}