View: List Claim type Research area Organism Taxon as written Decade Paper Method / resource observed original result measured Claim · model-written summary
Multi - environment models were similar to single- environment models when predicting unobserved phenotypes of untested entries.
performance of multi-environment models e0 single environment models e0 Not reported Taxon
Verbatim
e0 “performance of multi - environment models predicting unobserved phenotypes of untested entrees was similar to the performance of single environment models with differences in accuracy ranging from - 6% to 4% ”
✓ located verbatim in the source · abstract, characters 1272–1477 t0 “breeding rice for adaptation to alternate wetting and drying ”
✓ located verbatim in the source · abstract, characters 222–282 Other claims from this paper (3) Method / resource observed original result no effect measured Claim · model-written summary
Multi - environment models predicting unobserved phenotypes of untested entries performed similarly to single environment models , with predictive ability differences of -6-4%.
performance of multi-environment models e0 single environment models e0 Verbatim
e0 “performance of multi - environment models predicting unobserved phenotypes of untested entrees was similar to the performance of single environment models with differences in predictive ability ranging from -6-4% ”
✓ located verbatim in the source · abstract, characters 1241–1451 t0 “Rice ”
✓ located verbatim in the source · title, characters 216–220 Other claims from this paper (4) Method / resource observed original result positive simulated Claim · model-written summary
MTME models predicted genotype performance across simulated Mediterranean environment s, leveraging inter-trait and inter- environment covariance.
predictions of genotype performance e5 across simulated Mediterranean environments e5 single-environment (SE), multi-trait (MT), multi-environment (ME) e1 Verbatim
e2 “climate-resilient durum wheat improvement ”
✓ located verbatim in the source · abstract, characters 1241–1282 e1 “This study evaluates the performance of single- environment (SE), multi -trait (MT), multi - environment (ME), and multi -trait- multi - environment (MTME) genomic prediction models across seven key traits ”
✓ located verbatim in the source · abstract, characters 192–389 e5 “MTME models effectively leveraged inter-trait and inter- environment covariance, providing biologically realistic predictions of genotype performance across simulated Mediterranean environment s ”
✓ located verbatim in the source · abstract, characters 957–1149 Other claims from this paper (2) Method / resource observed original result positive measured Claim · model-written summary
Multi - environment models for entries assessed under both water systems outperformed single environment models by 30% on average.
predictive ability of multi-environment models e0 single environment models e0 Verbatim
e0 “predictive ability of multi - environment models predicting unobserved phenotypes of entrees evaluated under both water management systems outperformed single environment models by an average of 30% ”
✓ located verbatim in the source · abstract, characters 1519–1715 t0 “Rice ”
✓ located verbatim in the source · title, characters 216–220 Other claims from this paper (4) Method / resource observed original result positive measured Claim · model-written summary
MTME genomic prediction models achieved the highest prediction accuracy in durum wheat, particularly under CV2 and sowing-by-season grouping.
prediction accuracies e0 single-environment (SE), multi-trait (MT), multi-environment (ME) e1 Verbatim
e0 “MTME models achieved the highest prediction accuracies, particularly under CV2 and sowing-by-season grouping ”
✓ located verbatim in the source · abstract, characters 656–764 e1 “This study evaluates the performance of single- environment (SE), multi -trait (MT), multi - environment (ME), and multi -trait- multi - environment (MTME) genomic prediction models across seven key traits ”
✓ located verbatim in the source · abstract, characters 192–389 e2 “climate-resilient durum wheat improvement ”
✓ located verbatim in the source · abstract, characters 1241–1282 Other claims from this paper (2) Method / resource observed original result positive measured Claim · model-written summary
Accounting for genotype by environment interaction increased model performance .
accounting for genotype-by-environment interaction e0 performance of the models e0 Not reported Value
Verbatim
e0 “accounting for genotype-by- environment interaction also increased the performance of the models ”
✓ located verbatim in the source · abstract, characters 1281–1376 t0 “Pearl Millet ”
✓ located verbatim in the source · title, characters 31–43 Other claims from this paper (2) Method / resource observed original result positive measured Claim · model-written summary
The FA + G and FA + G + GG models displayed the best and a similar performance across all tests, compared with the Factor Analytic (FA) model.
Factor Analytic (FA) e1 Verbatim
t1 “Genomic Prediction from Multi - Environment Trials of Wheat Breeding ”
✓ located verbatim in the source · title, characters 0–66 e1 “Factor Analytic (FA), FA with genomic relationship matrix (FA + G) ”
✓ located verbatim in the source · abstract, characters 714–780 e2 “Results show that the FA + G and FA + G + GG models displayed the best and a similar performance across all tests ”
✓ located verbatim in the source · abstract, characters 907–1020 Other claims from this paper (4) Recommendation hypothesis original result basis n/a Claim · model-written summary
Incorporating environment al drivers of GEI into SNB risk models could enhance prediction accuracy.
prediction accuracy e6 Verbatim
t0 “Performance and Stability of Winter Wheat Cultivars to Stagonospora nodorum Blotch Epidemics in Multi - Environment Trials ”
✓ located verbatim in the source · title, characters 0–120 e6 “suggests that incorporating environment al drivers of GEI into SNB risk models could enhance prediction accuracy ”
✓ located verbatim in the source · abstract, characters 2091–2202 Other claims from this paper (5) Recommendation author interpretation original result basis n/a Claim · model-written summary
The authors concluded that robust prediction including dominance and epistasis requires deeper multi - environment phenotyping.
much deeper phenotyping in multi-environmental trials e0 Verbatim
e0 “robust hybrid prediction models , including dominance and epistatic effects, required much deeper phenotyping in multi - environment al trials ”
✓ located verbatim in the source · abstract, characters 1266–1404 t0 “Rapeseed ”
✓ located verbatim in the source · title, characters 41–49 Other claims from this paper (3) Method / resource observed original result positive measured Claim · model-written summary
Bayesian models had slightly higher imputation accuracy than non-Bayesian models .
accuracy of estimation performance e0 slightly higher e0 non-Bayesian analysis e0 Not reported Taxon
Verbatim
e0 “the models using Bayesian analysis had slightly higher accuracy of estimation performance than those using non-Bayesian analysis ”
✓ located verbatim in the source · abstract, characters 957–1085 Other claims from this paper (2) Lexical search (BM25). All words must match; if nothing does, any word. Organism names also match every spelling of the same organism. No semantic search yet.
Oryza sativa
Triticum turgidum subsp. durum
Cenchrus americanus
Triticum aestivum
Parastagonospora nodorum