{"id":"W3121740877","doi":"10.20944/preprints201811.0623.v1","title":"Evaluation of Genomic Prediction for Pasmo Resistance in Flax","year":2018,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Plant Disease Resistance and Genetics","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan; Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada; China Scholarship Council; Western Grains Research Foundation; Genome Canada","keywords":"Best linear unbiased prediction; Quantitative trait locus; Heritability; Population; Biology; Linear regression; Single-nucleotide polymorphism; Regression; Statistics; Genetics; Mathematics; Selection (genetic algorithm); Genotype; Machine learning; Computer science; Medicine; Gene","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":[0.00221673,0.0008120686,0.0004563101,0.0005934864,0.0001614305,0.000421061,0.0003904804,0.0005335819,0.0004223919],"category_scores_gemma":[0.002835238,0.0001683138,0.0005345377,0.000374731,0.0001441611,0.000297348,0.0003480508,0.0005220434,0.0002209809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004014881,"about_ca_system_score_gemma":0.0002923412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005260281,"about_ca_topic_score_gemma":0.004303229,"domain_scores_codex":[0.9994944,0.0002283159,0.00001967232,0.0001808054,0.00003982377,0.00003693649],"domain_scores_gemma":[0.9984593,0.001143763,0.0001018937,0.00009498858,0.0001548225,0.00004519716],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009135256,0.0004039358,0.1412968,0.0001261154,0.0005410514,0.0002044636,0.0001705549,0.6844534,0.03423967,0.0002768461,0.001284456,0.1360891],"study_design_scores_gemma":[0.00002107796,0.0001767593,0.05447067,0.00000843624,0.00006267915,0.00003677559,0.00002773295,0.9403381,0.004428389,0.0001965423,0.0002200513,0.00001270981],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9730443,0.000288119,0.02458519,0.00008385348,0.000007959235,0.00001747449,0.0008839029,0.0007217391,0.0003673729],"genre_scores_gemma":[0.9847076,0.0000543721,0.01232519,0.0000254121,0.000005103956,0.00001762524,0.002522389,0.00003593756,0.0003063742],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005260281,"threshold_uncertainty_score":0.01172334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1680669425514096,"score_gpt":0.3358617925236986,"score_spread":0.167794849972289,"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."}}