{"id":"W4401322700","doi":"10.1093/bioinformatics/btae483","title":"Cellular proliferation biases clonal lineage tracing and trajectory inference","year":2024,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Yale University","keywords":"Python (programming language); Computer science; Inference; Tracing; Probabilistic logic; Source code; Skew; Sampling bias; Theoretical computer science; Computational biology; Algorithm; Biology; Artificial intelligence; Statistics; Programming language; Mathematics; Sample size determination","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008295477,0.0007230661,0.0009040732,0.0008094955,0.001318587,0.002432276,0.002149491,0.001549721,0.00405853],"category_scores_gemma":[0.06013531,0.0006533319,0.0009484184,0.001551327,0.002048564,0.002208912,0.001942223,0.00199968,0.001056593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002350502,"about_ca_system_score_gemma":0.002538919,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.013987,"about_ca_topic_score_gemma":0.01280534,"domain_scores_codex":[0.9975925,0.0009137086,0.0001447366,0.0007071588,0.0004997599,0.0001421806],"domain_scores_gemma":[0.9644658,0.02844052,0.002617846,0.002354256,0.001630463,0.0004911834],"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":[0.0005062898,0.0001091783,0.1095197,0.001025752,0.0003507918,0.0006349679,0.000831852,0.6272604,0.02320019,0.1328791,0.01635237,0.08732933],"study_design_scores_gemma":[0.00004984112,0.00004498156,0.006723741,0.0001268345,0.00008867355,0.000402142,0.00008213815,0.8569738,0.0164281,0.110345,0.008670878,0.00006393114],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1129463,0.000980076,0.8724036,0.001964753,0.0001992306,0.0001424407,0.003634536,0.00368676,0.004042313],"genre_scores_gemma":[0.7804726,0.0009584524,0.2079837,0.0009843929,0.0002231473,0.0004226737,0.004810085,0.001150403,0.002994584],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.013987,"threshold_uncertainty_score":0.04387122,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02444510163836968,"score_gpt":0.2530713318885632,"score_spread":0.2286262302501935,"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."}}