{"id":"W4403609049","doi":"10.1186/s13059-024-03422-4","title":"Mapping lineage-traced cells across time points with moslin","year":2024,"lang":"en","type":"article","venue":"Genome biology","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"German Network for Bioinformatics Infrastructure; Azrieli Foundation; Council for Higher Education; Bundesministerium für Bildung und Forschung; Deutsche Forschungsgemeinschaft; European Commission; Joachim Herz Stiftung; Deutsches Zentrum für Herz-Kreislaufforschung; Wellcome Trust","keywords":"Biology; Evolutionary biology; Human genetics; Genome Biology; Lineage (genetic); Computational biology; Cell lineage; Computational genomics; Genomics; Genetics; Genome; Gene; Cellular differentiation","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001874198,0.0002912137,0.000236451,0.0003587905,0.0001990844,0.0003756811,0.000478168,0.000386685,0.0009012956],"category_scores_gemma":[0.0004011473,0.0002775426,0.0002192189,0.0002963227,0.0002988478,0.0003435583,0.0004453999,0.0003740459,0.0001605495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001003208,"about_ca_system_score_gemma":0.0003647025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002561685,"about_ca_topic_score_gemma":0.005954734,"domain_scores_codex":[0.9999378,0.000008435859,0.000002692513,0.00002554688,0.00001861814,0.000006860038],"domain_scores_gemma":[0.9998739,0.00004278534,0.00003673765,0.0000209921,0.00001014928,0.00001554606],"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":[0.0001599661,0.00003435148,0.004632877,0.00007293211,0.00002964515,0.0000950108,0.0001101726,0.17306,0.8021142,0.00493445,0.0003014048,0.01445492],"study_design_scores_gemma":[0.00001049259,0.00005710628,0.003625651,0.000005265176,0.000008180677,0.00004273882,0.00002878703,0.8530848,0.1399665,0.002029211,0.001121412,0.00001987437],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6916879,0.0001419039,0.305471,0.00009713219,0.00001850787,0.00002803625,0.0005044735,0.0008985585,0.001152555],"genre_scores_gemma":[0.8593587,0.0002006137,0.1385419,0.00003542326,0.000004819776,0.00007603873,0.000319116,0.0001877334,0.001275638],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002561685,"threshold_uncertainty_score":0.0072788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009446269006721865,"score_gpt":0.2384457908211804,"score_spread":0.2289995218144585,"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."}}