Try:droughtFusariumnitrogen fertilizerArabidopsisseed germination

“errors”

66 matches

Claim types

Direction of the findings

Over time

1960 ’70 ’80 ’90 2000 ’10 ’20

Refine ·

More filters

Clear filters

Method / resourceobservedoriginal resultno effectmeasured

Claim · model-written summary

Single-level storage errors produced little difference in latent and sensible heat flux errors.

Taxon: Rice Paddyt0
Outcome: errors in LE and He0
Direction: little differencese0
Qualifier: irrespective of timee0
Comparator: $F_s_{-single}$e0

Verbatim

e0
“there were little differences at the errors in LE and H caused by the error in $F_s_{-single}$, irrespective of time”
✓ located verbatim in the source · abstract, characters 3268–3384

t0
“Rice Paddy”
✓ located verbatim in the source · title, characters 143–153

Title

Errors in Net Ecosystem Exchanges of CO₂, Water Vapor, and Heat Caused by Storage Fluxes Calculated by Single-level Scalar Measurements Over a Rice Paddy

Minkyu Moon; Minseok Kang; Bindu Malla Thakuri; et al. Korean Journal of Agricultural and Forest Meteorology 2015. doi:10.5532/kjafm.2015.17.3.227

Other claims from this paper (6)

Observation Rates of change in CO2, water vapor and air temperature varied with height.
Method / resource Single-level storage flux estimates could be below or above profile estimates.
Method / resource Single-level estimates underestimated CO2 storage flux by 21% around sunrise and sunset.
Method / resource Single-level storage estimates underestimated CO2 exchange by 3% at night.
Method / resource Single-level storage estimates underestimated CO2 exchange by 2% around sunrise and sunset.
Mechanism The flux differences could lead to underestimation of rice paddy carbon balance during correction and partitioning.

Method / resourceobservedoriginal resultno effectmeasured

Claim · model-written summary

Direct and derived harvest index approaches had comparable errors.

Taxon: RiceOryza sativat0
Outcome: errorse0
Comparator: direct and derived HI approachese0

Verbatim

e0
“Both direct and derived HI approaches yielded comparable errors”
✓ located verbatim in the source · abstract, characters 2028–2091

t0
“Rice”
✓ located verbatim in the source · title, characters 77–81

Title

Multi-Source Time-Series Integration for Progressive In-Season Prediction of Rice Yield, Aboveground Biomass, and Harvest Index

Sunil Kumar Jha; James Brinkhoff; Andrew J. Robson; et al. Remote Sensing 2026. doi:10.3390/rs18111785

Other claims from this paper (9)

Method / resource March balanced forecast accuracy and lead time, with little later error reduction.
Method / resource TabPFN had the lowest yield prediction RMSE of 1.85 t ha−1.
Method / resource Ridge had the lowest biomass prediction RMSE of 3.05 t ha−1.
Method / resource Tree-based models had the lowest derived harvest index RMSE, about 0.07.
Method / resource Direct harvest index prediction had weak regional correlation of about 0.24.
Method / resource Derived harvest index prediction had regional correlation near zero.
Association Within site-seasons, harvest index correlated strongly with vegetation indices.
Observation The harvest index and vegetation index relationships varied greatly across site-seasons.
Recommendation The authors support satellite yield and biomass forecasting for operational use.

Method / resourceobservedoriginal resultno effectmeasured

Claim · model-written summary

Diameter errors were balanced when estimated against ground-truth values.

Outcome: Diameter errorse0
Direction: balancede0
Comparator: ground‐truth valuese1

Not reportedTaxon

Verbatim

e0
“Diameter errors were balanced”
✓ located verbatim in the source · abstract, characters 1038–1067

e1
“we compared the estimates of diameter, length and volume to ground‐truth values”
✓ located verbatim in the source · abstract, characters 701–780

Title

Accuracy of image analysis tools for functional root traits: A comment on Delory et al. (2017)

Laura Rose; Guillaume Lobet Methods in Ecology and Evolution 2019. doi:10.1111/2041-210x.13156

Other claims from this paper (15)

Method / resource WinRhizo and IJ_Rhizo gave comparable accuracy for diameter and length estimates at 1,200 and 800 dpi.
Method / resource Volume estimates had a systematic error caused by the assumption of constant diameter.
Observation WinRhizo provides the opportunity to calculate correctly computed volumes from diameter classes.
Observation At 1,200 dpi, IJ_Rhizo failed to find an appropriate threshold, which decreased accuracy.
Association The magnitude of diameter errors increased with root overlap for IJ_Rhizo.
Association Length errors of WinRhizo increased with root length, overlap and root length density.
Association The magnitude of WinRhizo volume underestimation decreased with volume.
Association Volume underestimation was higher for taproot than for fibrous root systems.
Association All errors increased with lower resolution.
Method / resource The results confirm the earlier accuracy results of Delory et al. for length.
Recommendation Estimates from different software packages or resolutions should not be compared directly.
Recommendation Characteristics of root systems should be standardised for image analysis.
Recommendation Methods should be validated for each analysed dataset.
Recommendation New image analysis tools should be validated against a real ground-truth.
Association The dependency of errors on the response variable of interest can increase the probability of errors.

Method / resourceobservedoriginal resultno effectmeasured

Claim · model-written summary

The methods had similar errors for liveweight gain per hectare.

Taxon: AlfalfaMedicago sativat0
Outcome: errors for gain per hae0
Direction: similare0
Comparator: the methodse0

Verbatim

e0
“the methods had similar errors for gain per ha.”
✓ located verbatim in the source · abstract, characters 971–1018

t0
“Alfalfa‐Orchardgrass”
✓ located verbatim in the source · title, characters 78–98

Title

Put‐and‐Take vs. Fixed Stocking for Defining Three Grazing Levels by Lambs on Alfalfa‐Orchardgrass¹

G. C. Marten; R. M. Jordan Agronomy Journal 1972. doi:10.2134/agronj1972.00021962006400010023x

Other claims from this paper (9)

Intervention effect The stocking methods yielded similar lamb daily and per-hectare liveweight gains over three years.
Association Greater grazing pressure or stocking rate decreased lamb daily gains.
Association Greater grazing pressure or stocking rate increased liveweight gains per hectare.
Observation Fixed stocking understocked early and overstocked late in the season.
Method / resource Fixed stocking produced lower experimental error for lamb daily gain.
Intervention effect After year one, alfalfa made up less of the mixture under light than heavy grazing.
Observation By year three, alfalfa percentage was nearly identical across treatments.
Recommendation Either stocking method can yield similar results if pasture yield potential is known.
Observation Fixed stocking has the disadvantage of requiring advance pasture yield-potential estimates.

Observationobservedoriginal resultno effectmeasured

Claim · model-written summary

Correlated errors did not differ across nitrogen conditions.

Taxon: cornZea mays subsp. mayst0
Outcome: correlated errorse0
Direction: no differencee0
Comparator: different N conditionse0

Verbatim

e0
“There was no difference in terms of correlated errors in experiments under different N conditions”
✓ located verbatim in the source · abstract, characters 1616–1713

t0
“corn”
✓ located verbatim in the source · title, characters 49–53

Title

Spatial variability in evaluation experiments of corn genotypes in the state of Mato Grosso do Sul, Brazil

Euriann Lopes Marques Yamamotto; Manoel Carlos Gonçalves; Livia Maria Chamma Davide; et al. Acta Scientiarum Agronomy 2022. doi:10.4025/actasciagron.v44i1.55972

Other claims from this paper (3)

Method / resource Error and genotype mean-square differences were slightly more evident in experiments 1–6 and 11.
Method / resource ANOVA-AR did not produce major changes in the corn trial analyses.
Method / resource ANOVA-AR and traditional ANOVA gave similar experimental precision parameter values.

Method / resourceobservedoriginal resultno effectmeasured

Claim · model-written summary

Large trees did not substantially affect estimation errors.

Taxon: CassavaManihot esculentat0
Outcome: estimation errorse0
Direction: did not substantially affecte0
Comparator: Cassavat0

Verbatim

e0
“it did not substantially affect estimation errors”
✓ located verbatim in the source · abstract, characters 1484–1533

t0
“Evaluation of Sentinel-2 Vegetation Indices for Estimating Leaf Area Index in Cassava Plots”
✓ located verbatim in the source · title, characters 0–91

Title

Evaluation of Sentinel-2 Vegetation Indices for Estimating Leaf Area Index in Cassava Plots

Kanokporn Promnikorn; Thanpitcha Jenkit; Piya Kittipadakul; et al. AgriEngineering 2026. doi:10.3390/agriengineering8040134

Other claims from this paper (7)

Method / resource GNDVI performed best across growth stages for cassava LAI estimation.
Method / resource NDWI performed best across growth stages for cassava LAI estimation.
Method / resource SeLI followed GNDVI and NDWI in performance.
Method / resource Ratio Vegetation Index performed best at two months after planting.
Method / resource GNDVI and NDWI excelled during mid-growth at three to five months after planting.
Method / resource SeLI excelled at seven months after planting.
Method / resource Large trees altered vegetation-index performance ranking.

Method / resourceobservedoriginal resultno effectsimulated

Claim · model-written summary

Mapmaker and the MCMC method performed similarly without genotyping errors.

Outcome: performancee0
Direction: similare0
Comparator: Mapmakere0

Not reportedTaxon

Verbatim

e0
“the performance is similar between Mapmaker and the MCMC-based method in the absence of genotyping errors”
✓ located verbatim in the source · abstract, characters 745–850

Title

Bayesian and maximum likelihood estimation of genetic maps

THOMAS L. YORK; RICHARD T. DURRETT; STEVEN TANKSLEY; et al. Genetics Research 2005. doi:10.1017/s0016672305007494

Other claims from this paper (4)

Method / resource The MAP estimator performed better than estimators based on posterior expectation.
Method / resource The MCMC method had an advantage over Mapmaker when genotyping errors were present.
Method / resource The Bayesian method showed no similar advantage for missing data.
Method / resource On eggplant data, the MCMC method gave smaller genetic distance estimates.

Associationobservedoriginal resultno effectnot significant (as stated)measured

Claim · model-written summary

Time since calibration had no significant effect on load prediction errors.

Taxon: CottonGossypium hirsutumt0
Outcome: load prediction errorse0
Direction: nosignificant effecte0
Qualifier: time elapsed since last system calibratione0

Not reportedSetting

Verbatim

e0
“the amount of time elapsed since last system calibration had nosignificant effect on load prediction errors”
✓ located verbatim in the source · abstract, characters 913–1020

t0
“Cotton Yield Mapping”
✓ located verbatim in the source · title, characters 60–80

Title

Development and Evaluation of a Flow Measurement Device for Cotton Yield Mapping

John B. Wilkerson; F. Henry Moody; William E. Hart 2001 Sacramento, CA July 29-August 1,2001 2001. doi:10.13031/2013.5522

Other claims from this paper (6)

Method / resource Integrated cotton flow measurements predicted load mass with mean error of 4.0 percent.
Method / resource Debris accumulation on sensor faces did not degrade performance across harvest seasons.
Association Average cotton flow rate had no significant effect on load prediction errors.
Association Cotton moisture content had no significant effect on load prediction errors.
Association Cotton variety significantly affected load prediction errors.
Recommendation The authors recommend checking calibration when the harvested cotton variety changes.

Associationobservedoriginal resultno effectnot significant (as stated)measured

Claim · model-written summary

Cotton moisture content had no significant effect on load prediction errors.

Taxon: CottonGossypium hirsutumt0
Organ / stage: cottone0
Outcome: load prediction errorse0
Direction: nosignificant effecte0

Verbatim

e0
“Average cotton flow rate, cottonmoisture content, and the amount of time elapsed since last system calibration had nosignificant effect on load prediction errors”
✓ located verbatim in the source · abstract, characters 859–1020

t0
“Cotton Yield Mapping”
✓ located verbatim in the source · title, characters 60–80

Title

Development and Evaluation of a Flow Measurement Device for Cotton Yield Mapping

John B. Wilkerson; F. Henry Moody; William E. Hart 2001 Sacramento, CA July 29-August 1,2001 2001. doi:10.13031/2013.5522

Other claims from this paper (6)

Method / resource Integrated cotton flow measurements predicted load mass with mean error of 4.0 percent.
Method / resource Debris accumulation on sensor faces did not degrade performance across harvest seasons.
Association Average cotton flow rate had no significant effect on load prediction errors.
Association Time since calibration had no significant effect on load prediction errors.
Association Cotton variety significantly affected load prediction errors.
Recommendation The authors recommend checking calibration when the harvested cotton variety changes.

Associationobservedoriginal resultno effectnot significant (as stated)measured

Claim · model-written summary

Average cotton flow rate had no significant effect on load prediction errors.

Taxon: CottonGossypium hirsutumt0
Outcome: load prediction errorse0
Direction: nosignificant effecte0
Qualifier: Average cotton flow ratee0

Not reportedSetting

Verbatim

e0
“Average cotton flow rate, cottonmoisture content, and the amount of time elapsed since last system calibration had nosignificant effect on load prediction errors”
✓ located verbatim in the source · abstract, characters 859–1020

t0
“Cotton Yield Mapping”
✓ located verbatim in the source · title, characters 60–80

Title

Development and Evaluation of a Flow Measurement Device for Cotton Yield Mapping

John B. Wilkerson; F. Henry Moody; William E. Hart 2001 Sacramento, CA July 29-August 1,2001 2001. doi:10.13031/2013.5522

Other claims from this paper (6)

Method / resource Integrated cotton flow measurements predicted load mass with mean error of 4.0 percent.
Method / resource Debris accumulation on sensor faces did not degrade performance across harvest seasons.
Association Cotton moisture content had no significant effect on load prediction errors.
Association Time since calibration had no significant effect on load prediction errors.
Association Cotton variety significantly affected load prediction errors.
Recommendation The authors recommend checking calibration when the harvested cotton variety changes.

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.

“errors”

Claim types

Direction of the findings

Over time

Claim type

Research area

Polarity

Statistics