{"id":"W4385173870","doi":"10.1101/2023.07.20.549801","title":"Cellular proliferation biases clonal lineage tracing and trajectory inference","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Inference; Tracing; Trajectory; Lineage (genetic); Statistical inference; Probabilistic logic; clone (Java method); Computer science; Simple (philosophy); Cell lineage; Algorithm; Biology; Artificial intelligence; Statistics; Mathematics; Gene; Genetics; Cellular differentiation; Physics","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":[0.008805102,0.0005579551,0.0008294907,0.0009610128,0.0008642384,0.00201789,0.001536202,0.001494983,0.001767867],"category_scores_gemma":[0.05961752,0.0006687301,0.0006186312,0.001266612,0.002020503,0.002314379,0.001757365,0.001754905,0.000331429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002161937,"about_ca_system_score_gemma":0.001607382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006216371,"about_ca_topic_score_gemma":0.005055856,"domain_scores_codex":[0.9964942,0.001509783,0.0001544593,0.0007631013,0.0008865373,0.0001919361],"domain_scores_gemma":[0.9526975,0.03787226,0.004003338,0.003291658,0.001673177,0.0004620006],"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":[0.0003359801,0.00009088538,0.06055731,0.0002817482,0.0002469874,0.0003890649,0.0005555297,0.6405574,0.05793471,0.1708073,0.002169677,0.06607337],"study_design_scores_gemma":[0.00001723796,0.00002834865,0.004823538,0.00002850491,0.00003263451,0.0001273699,0.00003318255,0.908882,0.02253115,0.06208795,0.001372605,0.00003539066],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1493828,0.000316012,0.8465011,0.0006616209,0.00005306166,0.00003531757,0.0002847612,0.0007352196,0.002030072],"genre_scores_gemma":[0.8929952,0.0003372211,0.104229,0.0002742922,0.00006578645,0.0000822923,0.000380425,0.000342317,0.001293374],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008805102,"threshold_uncertainty_score":0.04656637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03117482365183011,"score_gpt":0.238371579869583,"score_spread":0.2071967562177529,"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."}}