{"id":"W2890135776","doi":"10.1038/s41598-018-31963-9","title":"Genetic diversity and phylogeny of South African Meloidogyne populations using genotyping by sequencing","year":2018,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Nematode management and characterization studies","field":"Agricultural and Biological Sciences","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"National Research Foundation","keywords":"Genotyping; Genetic diversity; Phylogenetics; Biology; Evolutionary biology; Diversity (politics); DNA sequencing; Genotype; Genetics; Medicine; Population; Gene; Anthropology","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0002427099,0.00006580499,0.0001042347,0.00002048962,0.00141741,0.00005841155,0.00006324852,0.0000209044,0.0000883293],"category_scores_gemma":[0.00002315851,0.00003132551,0.00002768131,0.0003405568,0.0002333598,0.00007907841,0.0003899423,0.00001897383,0.000001366727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000146351,"about_ca_system_score_gemma":0.000004060586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001677956,"about_ca_topic_score_gemma":0.00009079236,"domain_scores_codex":[0.999172,0.00001972103,0.000201669,0.0002912126,0.0001828498,0.0001325754],"domain_scores_gemma":[0.9995574,0.000008475128,0.0002136984,0.00006982388,0.0001121192,0.00003849507],"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":[0.000001606287,0.000007885737,0.1737253,0.000005521782,0.000008535788,0.000003616713,0.001156363,0.000002660633,0.8235507,0.00002278187,0.0001444347,0.001370568],"study_design_scores_gemma":[0.00006307414,0.00004891598,0.9713234,0.00003072953,0.00006683767,0.00002119042,0.002795106,0.0004916252,0.0197619,0.002548351,0.002581065,0.0002678014],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988621,0.00007498849,0.00009768151,0.00002723051,0.0005269715,0.0001010775,0.000006200834,0.00002055321,0.000283225],"genre_scores_gemma":[0.9994054,0.000001871447,0.000269423,0.00001574635,0.00005669559,9.359199e-7,0.00001308368,4.96036e-7,0.0002363362],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8037888,"threshold_uncertainty_score":0.9998826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06248345242248022,"score_gpt":0.2336014558693457,"score_spread":0.1711180034468655,"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."}}