{"id":"W4220992271","doi":"10.1101/2022.03.10.483676","title":"Focusing the GWAS <i>Lens</i> on days to flower using latent variable phenotypes derived from global multi-environment trials","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genetic and Environmental Crop Studies","field":"Agricultural and Biological Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Saskatchewan Pulse Growers; Genome Prairie; Western Grains Research Foundation; University of Saskatchewan; Genome Canada","keywords":"Biology; Germplasm; Phenology; Quantitative trait locus; Genome-wide association study; Trait; Phenotypic trait; Genetic diversity; Adaptation (eye); Phenotype; Evolutionary biology; Genetics; Ecology; Gene; Single-nucleotide polymorphism; Genotype; Agronomy; Demography","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":[0.004455796,0.0008244334,0.000778033,0.0006831836,0.0005232487,0.001262759,0.0006815831,0.0004363493,0.003400998],"category_scores_gemma":[0.003611239,0.0002473503,0.001961475,0.001350802,0.0005875718,0.0004486972,0.0009243921,0.000918037,0.0003106635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003657441,"about_ca_system_score_gemma":0.0006405233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005038188,"about_ca_topic_score_gemma":0.01449666,"domain_scores_codex":[0.9973732,0.001438795,0.0001231809,0.0007445012,0.0001664318,0.000153806],"domain_scores_gemma":[0.9949675,0.002841142,0.0007323772,0.00100825,0.0002194776,0.0002312047],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003078461,0.0002921567,0.7887245,0.0005998433,0.007743067,0.0006090028,0.0003505423,0.009048316,0.1441245,0.002310014,0.004090087,0.03902953],"study_design_scores_gemma":[0.000149147,0.0006511305,0.9651251,0.00005052793,0.002326242,0.0002455072,0.000160682,0.01550466,0.008147215,0.00127198,0.006305751,0.00006189183],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.8982591,0.0006544986,0.08020401,0.0005841226,0.00008378813,0.0001674715,0.01641217,0.0008898253,0.002745129],"genre_scores_gemma":[0.9697933,0.000109111,0.02291865,0.0004008969,0.00003272641,0.0002370275,0.005306988,0.0002743352,0.0009269372],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.005038188,"threshold_uncertainty_score":0.02356476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05363757631437673,"score_gpt":0.2286582844872676,"score_spread":0.1750207081728909,"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."}}