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Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Cross-validation prediction errors were similar to fitting errors.

Outcome
root mean squared errors of prediction (RMSEPs)e0
Direction
similare0
Comparator
fitting errorse0

Verbatim

e0

“The root mean squared errors of prediction (RMSEPs) were similar to fitting errors”

✓ located verbatim in the source · abstract, characters 1002–1084

Title

Estimating Genetic Coefficients for the CSM‐CERES‐Maize Model in North Carolina Environments

Zhengyu Yang; Gail G. Wilkerson; Gregory S. Buol; et al. Agronomy Journal 2009. doi:10.2134/agronj2008.0234x

Other claims from this paper (3)
Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Cross-validation errors were similar to errors from independent data.

Outcome
errorse0
Direction
similare0
Comparator
independent datae0

Verbatim

e0

“These errors were similar to those computed using independent data.”

✓ located verbatim in the source · abstract, characters 1275–1342

Title

Evaluating Methods for Simulating Soybean Cultivar Responses Using Cross Validation

Ayse Irmak; James W. Jones; Theodoros Mavromatis; et al. Agronomy Journal 2000. doi:10.2134/agronj2000.9261140x

Other claims from this paper (3)
Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Thermal conductance estimation errors were similar in order to porometer measurement errors.

Taxon
vineyarde1
Outcome
errors in thermal estimates of conductancee0
Comparator
measurement errors using a porometere0
Setting
Southern Portugale1

Verbatim

e0

“The errors in thermal estimates of conductance were of the same order as the measurement errors using a porometer”

✓ located verbatim in the source · abstract, characters 683–796
e1

“measured gs data from a vineyard in Southern Portugal”

✓ located verbatim in the source · abstract, characters 628–681

Title

Estimating stomatal conductance with thermal imagery

I. LEINONEN; O. M. GRANT; C. P. P. TAGLIAVIA; et al. Plant Cell & Environment 2006. doi:10.1111/j.1365-3040.2006.01528.x

Other claims from this paper (5)
Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Nutrient delivery errors were in part due to inaccuracies in the tank concentrations rather than operational errors.

Taxon
willowSalixt0
Outcome
errorse2
Qualifier
inaccuracies in the tank concentrationse2
Comparator
operational errorse2

Verbatim

t0

“Computer-Controlled Delivery of Five Levels of Nutrients to Container-Grown Willow”

✓ located verbatim in the source · title, characters 0–82
e2

“the errors were in part due to inaccuracies in the tank concentrations rather than operational errors”

✓ located verbatim in the source · abstract, characters 848–949

Title

Computer-Controlled Delivery of Five Levels of Nutrients to Container-Grown Willow

Jessica J. Prenger; Robert C. Hansen; Carolyn Glynn; et al. 2001 Sacramento, CA July 29-August 1,2001 2001. doi:10.13031/2013.7499

Other claims from this paper (1)
Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Prototype testing recorded four communication errors in 10,250 operations.

Outcome
communication errorse0
Value
four communication errorse0
Qualifier
10,250 operationse0

Not reportedComparator

Verbatim

e0

“four communication errors and three valve errors occurred out of 10,250 operations”

✓ located verbatim in the source · abstract, characters 894–976
e1

“nectarine orchard”

✓ located verbatim in the source · abstract, characters 150–167

Title

Design of a System for Individual Microsprinkler Control

R. W. Coates; M. J. Delwiche; P. H. Brown Transactions of the ASABE 2006. doi:10.13031/2013.22276

Other claims from this paper (5)
Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Prototype testing recorded three valve errors in 10,250 operations.

Outcome
valve errorse0
Value
three valve errorse0
Qualifier
10,250 operationse0

Not reportedComparator

Verbatim

e0

“four communication errors and three valve errors occurred out of 10,250 operations”

✓ located verbatim in the source · abstract, characters 894–976
e1

“nectarine orchard”

✓ located verbatim in the source · abstract, characters 150–167

Title

Design of a System for Individual Microsprinkler Control

R. W. Coates; M. J. Delwiche; P. H. Brown Transactions of the ASABE 2006. doi:10.13031/2013.22276

Other claims from this paper (5)
Method / resourceobservedoriginal resultpositivebasis n/a

Claim · model-written summary

The filtering routine comprised seven steps targeting different errors.

Outcome
different errorse0
Value
seven stepse0

Not reportedTaxon

Verbatim

e0

“The routine has seven steps, each one acting over different errors.”

✓ located verbatim in the source · abstract, characters 897–964

Title

Methodology for identification, characterization and removal of errors on yield maps

José Paulo Molin; L. A. A. Menegatti 2002

Other claims from this paper (3)
Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

NIRS prediction errors were less than twice laboratory measurement errors.

Taxon
Populus spp.Populust0
Outcome
standard errors of prediction (SEP)e0
Direction
less than twicee0
Comparator
corresponding laboratory measuremente0

Verbatim

e0

“the standard errors of prediction (SEP) obtained from the NIRS calibration models were less than twice those of the corresponding laboratory measurement.”

✓ located verbatim in the source · abstract, characters 987–1140
t0

“Populus spp.”

✓ located verbatim in the source · title, characters 29–41

Title

Analysis of Energy Traits of Populus spp. Clones by Near-Infrared Spectroscopy

Melchor C. Maranan; Marie-Pierre G. Laborie Journal of Biobased Materials and Bioenergy 2007. doi:10.1166/jbmb.2007.1989

Other claims from this paper (8)
Method / resourceobservedoriginal resultsimulated

Claim · model-written summary

Emission factor errors were the largest source of uncertainty, followed by temperature and foliar biomass errors.

Taxon
forestst0
Outcome
Largest uncertaintye0
Comparator
errors in temperature and foliar biomasse0

Verbatim

t0

“forests”

✓ located verbatim in the source · title, characters 86–93
e0

“Largest uncertainty results from errors of the emission factors followed by errors in temperature and foliar biomass.”

✓ located verbatim in the source · abstract, characters 1434–1551

Title

Uncertainty assessment of potential biogenic volatile organic compound emissions from forests with the Monte Carlo method: Case study for an episode from 1 to 10 July 2000 in Poland

G. Smiatek; M. Bogacki Journal of Geophysical Research Atmospheres 2005. doi:10.1029/2004jd005685

Other claims from this paper (6)
Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Summertime (June to September) cloud-originated errors explained 78% of the annual accumulated GPP error.

Outcome
annual accumulative errors in GPPe2
Value
78%e2
Qualifier
Summertime errors from June to Septembere2

Not reportedTaxon

Verbatim

e2

“Summertime errors from June to September explained by 78% of the annual accumulative errors in GPP”

✓ located verbatim in the source · abstract, characters 1404–1502

Title

Analysis on Cloud-Originated Errors of MODIS Leaf Area Index and Primary Production Images: Effect of Monsoon Climate in Korea

Sin-Kyu Kang The Korean Journal of Ecology 2005. doi:10.5141/jefb.2005.28.4.215

Other claims from this paper (7)

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