{"id":"W2884300026","doi":"10.1002/aps3.1164","title":"flowPloidy: An R package for genome size and ploidy assessment of flow cytometry data","year":2018,"lang":"en","type":"article","venue":"Applications in Plant Sciences","topic":"Chromosomal and Genetic Variations","field":"Agricultural and Biological Sciences","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Agriculture and Agri-Food Canada","funders":"","keywords":"Workflow; Histogram; Genome size; Biology; Genome; Software; R package; Computer science; Ploidy; Data mining; Computational biology; Artificial intelligence; Database; Genetics; Computational science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004534298,0.00007092882,0.0001086116,0.00002184791,0.0003238301,0.00004809298,0.0005991683,0.00003747165,0.0000590843],"category_scores_gemma":[0.00004550559,0.00003019406,0.00001335092,0.0005903113,0.0002683604,0.0001569396,0.0001370029,0.0000317468,0.000001977515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008856381,"about_ca_system_score_gemma":0.00002402311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001439354,"about_ca_topic_score_gemma":0.002218443,"domain_scores_codex":[0.9991167,0.000022989,0.0001848496,0.0003730257,0.0001466417,0.0001558277],"domain_scores_gemma":[0.9992424,0.0004523479,0.00006868858,0.0001419895,0.00004087575,0.00005367689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0000077124,0.0003942232,0.1060933,0.00001486707,0.00001156179,2.140546e-7,0.0002890885,0.00001466902,0.8674592,0.009191634,0.00005869119,0.01646491],"study_design_scores_gemma":[0.0001088763,0.0003630652,0.9793274,0.000007553665,0.00001083026,0.000003884408,0.0005482617,0.007054034,0.001550882,0.003969715,0.006920759,0.0001347413],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957418,0.00005169667,0.0009521941,0.0004561866,0.00003157104,0.0004233624,0.001910209,0.0000186682,0.0004143521],"genre_scores_gemma":[0.9817066,0.00003850996,0.01756334,0.00005131674,0.0001387575,0.0000792932,0.0004075988,4.754563e-7,0.00001408416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8732342,"threshold_uncertainty_score":0.2490672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06643705613624745,"score_gpt":0.3181980956890477,"score_spread":0.2517610395528003,"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."}}