{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001792589,0.0001778764,0.0002191429,0.0001044823,0.00004866913,0.000009243993,0.0001558018,0.0004291827,0.00001639123],"category_scores_gemma":[0.0000122406,0.0001467676,0.00005973523,0.0001099196,0.00006178496,0.00001767384,0.00002880492,0.0001115413,0.00001354152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005365877,"about_ca_system_score_gemma":0.00002512421,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001384694,"about_ca_topic_score_gemma":0.0009822538,"domain_scores_codex":[0.9985924,0.0001734077,0.0003583572,0.000441568,0.00003317412,0.0004011111],"domain_scores_gemma":[0.9996169,0.000037202,0.00009596508,0.0001983849,0.00001761145,0.00003396233],"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":[0.0002120629,0.00007561286,0.03946553,0.00001215625,0.00000663535,0.000007385324,0.0001952978,0.0002906473,0.9593251,0.00003332316,0.00007085262,0.0003054395],"study_design_scores_gemma":[0.0040037,0.001180578,0.1266369,0.00002408254,0.00002485974,0.00004224825,0.0001351971,0.0003071498,0.8525628,0.0009164792,0.01342218,0.0007437924],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950053,0.0007312844,0.002434899,0.001030706,0.0002629343,0.0001982742,0.00007265688,0.0000136886,0.0002502456],"genre_scores_gemma":[0.9980541,0.0001262693,0.00005574039,0.0007126018,0.0001589937,0.00001422245,0.0004542125,0.0000163359,0.0004074563],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1067623,"threshold_uncertainty_score":0.5985009,"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."}}