{"id":"W1826286403","doi":"10.1002/cyto.a.22718","title":"Endopolyploidy, genome size, and flow cytometry","year":2015,"lang":"en","type":"article","venue":"Cytometry Part A","topic":"Chromosomal and Genetic Variations","field":"Agricultural and Biological Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Genome size; Flow cytometry; Computational biology; Genome; Cytometry; Biology; Genetics; Gene","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002087512,0.0001380295,0.0001761817,0.00002609216,0.0001487622,0.00008230712,0.0001671666,0.00008943725,0.0008333448],"category_scores_gemma":[0.0002335068,0.00005686649,0.00005607003,0.0008704325,0.00006691348,0.000092014,0.0001333052,0.00009276907,0.0002578894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000256047,"about_ca_system_score_gemma":0.00001375268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003645266,"about_ca_topic_score_gemma":0.00005261591,"domain_scores_codex":[0.9989685,0.00004442634,0.0001781761,0.0002919316,0.0002334882,0.0002834592],"domain_scores_gemma":[0.9992778,0.0002070209,0.00004905439,0.00007428192,0.00006893977,0.0003228432],"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":[0.00007924916,0.0004120133,0.1066457,0.00001982161,0.0001025242,0.00004630475,0.0005891054,0.00002279284,0.8358144,0.0005315382,0.002823558,0.05291302],"study_design_scores_gemma":[0.0006379284,0.0005073345,0.6449721,0.00001247806,0.00003560329,0.0000976473,0.0005748229,0.0001582581,0.00311473,0.001750691,0.3476737,0.0004646464],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928178,0.0008682744,0.00001538561,0.0008884943,0.0002318566,0.0001338352,0.0001058418,0.00009556331,0.004842943],"genre_scores_gemma":[0.997027,0.00005531318,0.0005979156,0.000317548,0.000663061,0.00001629909,0.00004578553,0.000001319678,0.001275762],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8326997,"threshold_uncertainty_score":0.9124541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03382553934634237,"score_gpt":0.2306427471626357,"score_spread":0.1968172078162934,"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."}}