{"id":"W2345383806","doi":"10.1186/s13059-016-0937-9","title":"In silico lineage tracing through single cell transcriptomics identifies a neural stem cell population in planarians","year":2016,"lang":"en","type":"article","venue":"Genome biology","topic":"Planarian Biology and Electrostimulation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":97,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hospital for Sick Children; Ontario Institute for Cancer Research; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Ontario Institute for Cancer Research","keywords":"Biology; In silico; Evolutionary biology; Cell lineage; Lineage (genetic); Transcriptome; Population; Stem cell; Neural stem cell; Computational biology; Cell; Human genetics; Zebrafish; Planarian; Genetics; Regeneration (biology); Gene; Cellular differentiation","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":[0.0002197888,0.0003141443,0.0002451511,0.0004916905,0.0002771002,0.0005165639,0.0002799354,0.0002947972,0.0004830208],"category_scores_gemma":[0.0004528338,0.0001831244,0.0004424479,0.000320804,0.0002947401,0.0001930366,0.0002388913,0.0002908355,0.0002858865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003525053,"about_ca_system_score_gemma":0.0003719142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001791426,"about_ca_topic_score_gemma":0.00394907,"domain_scores_codex":[0.9998591,0.00001547263,0.000007612269,0.00005429015,0.00004523877,0.00001819665],"domain_scores_gemma":[0.9998152,0.00008741708,0.00003899695,0.0000167859,0.0000285295,0.00001320631],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008506967,0.000008133954,0.007566283,0.00008849964,0.00001995951,0.00005461761,0.00006160896,0.003217492,0.9821014,0.0001563045,0.00007030337,0.006570401],"study_design_scores_gemma":[0.00001215698,0.0001641563,0.0967024,0.00001757264,0.00009830896,0.0003205958,0.0002194259,0.07705084,0.8199958,0.0007006906,0.004690631,0.00002738831],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9561141,0.0003491431,0.04004265,0.00006862216,0.000006087113,0.00002526065,0.002279162,0.0006026929,0.0005123029],"genre_scores_gemma":[0.9209698,0.0006326663,0.06796395,0.0000832341,0.000007310744,0.00007459307,0.009125393,0.0001891005,0.0009539202],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001791426,"threshold_uncertainty_score":0.003561974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0135694092754785,"score_gpt":0.2295820634558934,"score_spread":0.2160126541804149,"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."}}