{"id":"W2099306768","doi":"10.1590/s0103-84782004000200026","title":"Genetic variation and correlation of agronomic traits in meadow bromegrass (Bromus riparius Rehm) clones","year":2004,"lang":"en","type":"article","venue":"Ciência Rural","topic":"Turfgrass Adaptation and Management","field":"Environmental Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Heritability; Biology; Bromus; Agronomy; Pasture; Bromus inermis; Forage; Cultivar; Genetic variation; Genetic variability; Genetic correlation; Dry matter; Germplasm; Genetic gain; Poaceae; Genotype; Genetics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004753563,0.000287828,0.0002738407,0.001174624,0.0003163313,0.0003141707,0.000198717,0.0002092429,0.0005758456],"category_scores_gemma":[0.0007917141,0.0001683136,0.0001739968,0.000500443,0.0003474173,0.00008556946,0.0002882638,0.000188377,0.000130143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003441059,"about_ca_system_score_gemma":0.0001542624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005531263,"about_ca_topic_score_gemma":0.0124084,"domain_scores_codex":[0.9995752,0.00008716653,0.00002987823,0.0001370036,0.0001222713,0.00004851298],"domain_scores_gemma":[0.9994459,0.0002062108,0.000133699,0.00006443042,0.00006646153,0.00008336231],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007032895,0.0001940592,0.6985646,0.00003424982,0.0003300954,0.0006469843,0.001694174,0.0004833003,0.284343,0.0001437698,0.00007204479,0.01279055],"study_design_scores_gemma":[0.000006809877,0.00007675408,0.9981889,0.000001849824,0.00001796444,0.0001925199,0.00009126429,0.0002253687,0.001062465,0.00001428522,0.0001170364,0.000004675221],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.999835,0.00001869694,0.0000518517,0.000001225589,3.222408e-7,0.000001784652,0.00003005409,0.000001976547,0.00005894077],"genre_scores_gemma":[0.9992347,0.00003186097,0.0002539075,0.000003245015,9.6575e-7,0.000006253738,0.0002417222,0.000005832305,0.0002215871],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005531263,"threshold_uncertainty_score":0.01099813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00592491246177908,"score_gpt":0.1911644234961513,"score_spread":0.1852395110343722,"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."}}