{"id":"W3046469654","doi":"10.1101/2020.07.31.231621","title":"A Unified Framework for Lineage Tracing and Trajectory Inference","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Single-cell and spatial transcriptomics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Royal Commission for the Exhibition of 1851; Natural Sciences and Engineering Research Council of Canada; Burroughs Wellcome Fund","keywords":"Tracing; Inference; Lineage (genetic); Trajectory; Computer science; Leverage (statistics); Theoretical computer science; Artificial intelligence; Biology; Gene; Genetics","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":[0.00673497,0.001591596,0.001840528,0.003881902,0.001556978,0.004042715,0.004839276,0.002618975,0.00502129],"category_scores_gemma":[0.01693995,0.001729712,0.003651003,0.002761865,0.002882463,0.004045383,0.006156661,0.005233638,0.001552366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003435274,"about_ca_system_score_gemma":0.005690263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01525475,"about_ca_topic_score_gemma":0.0134343,"domain_scores_codex":[0.9969337,0.00116195,0.0002350471,0.0006680115,0.0007926571,0.0002085787],"domain_scores_gemma":[0.9926091,0.004141849,0.0006156243,0.0009701854,0.001263499,0.0003996408],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00004738911,0.0000406979,0.0008489094,0.0001221488,0.0000755804,0.0001466603,0.0001600368,0.4250608,0.001808175,0.5400572,0.0016955,0.02993693],"study_design_scores_gemma":[0.000009855719,0.00001242487,0.00005479655,0.00002713971,0.00001189598,0.0000299565,0.00001474275,0.8556837,0.0005274022,0.1407497,0.002862298,0.00001611955],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003113601,0.00004646153,0.9991344,0.00006502873,0.000009765864,0.000009893484,0.00006342349,0.000126329,0.0002334616],"genre_scores_gemma":[0.04906587,0.0004550272,0.9465418,0.0001290895,0.0001003775,0.0002777899,0.0008915847,0.0004192667,0.002119231],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01525475,"threshold_uncertainty_score":0.03561836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02571230152011791,"score_gpt":0.2461365681059559,"score_spread":0.220424266585838,"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."}}