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Observationobservedoriginal resultmeasured

Claim · model-written summary

Segmentation misclassification and mosaicking errors contributed mainly to detection errors.

Taxon
sorghumSorghumt0
Outcome
panicle detection errorse0
Qualifier
Misclassifications of panicles during the semantic segmentation step and mosaicking errors in the field orthomosaice0

Verbatim

e0

“Misclassifications of panicles during the semantic segmentation step and mosaicking errors in the field orthomosaic contributed mainly to panicle detection errors”

✓ located verbatim in the source · abstract, characters 1693–1855
t0

“Sorghum”

✓ located verbatim in the source · title, characters 69–76

Title

A Deep Learning Semantic Segmentation-Based Approach for Field-Level Sorghum Panicle Counting

Lonesome Malambo; Sorin Popescu; Nian-Wei Ku; et al. Remote Sensing 2019. doi:10.3390/rs11242939

Other claims from this paper (3)
Associationauthor interpretationoriginal resultnegativebasis n/a

Claim · model-written summary

The dependency of errors on the response variable of interest can increase the probability of errors.

Treatment
dependency of errors on the response variable of intereste0
Outcome
probability of errorse0
Direction
increasee0

Not reportedTaxon

Verbatim

e0

“The dependency of errors on the response variable of interest can influence the effect size and increase the probability of errors”

✓ located verbatim in the source · abstract, characters 2093–2223

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 / 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 resultnegativesignificant (as stated)simulated

Claim · model-written summary

Temperature data errors influenced both crop models significantly more than precipitation errors.

Taxon
cropt0
Outcome
influence on both modelse0
Direction
strongere0
Comparator
errors in precipitatione0

Verbatim

e0

“errors in temperature data have a significantly stronger influence on both models than errors in precipitation”

✓ located verbatim in the source · abstract, characters 521–631
t0

“a process-based crop model and a statistical crop model”

✓ located verbatim in the source · abstract, characters 451–506

Title

Comparing the effects of calibration and climate errors on a statistical crop model and a process-based crop model

James Watson; Andrew J. Challinor; Thomas E. Fricker; et al. Climatic Change 2014. doi:10.1007/s10584-014-1264-3

Other claims from this paper (4)
Associationobservedoriginal resultsimulated

Claim · model-written summary

Simulated leaf area index errors were associated with daily simulated ET errors, varying by growth stage.

Organ / stage
growth stagee0
Outcome
errors in daily simulated ETe0
Qualifier
Errors in simulated leaf area indexe0

Not reportedDirection

Verbatim

e0

“Errors in simulated leaf area index were associated with errors in daily simulated ET, but the relationship varied with the growth stage”

✓ located verbatim in the source · abstract, characters 1671–1807
t0

“Wheat crop models”

✓ located verbatim in the source · title, characters 0–17

Title

Wheat crop models underestimate drought stress in semi-arid and Mediterranean environments

H. Webber; D. Cooke; C. Wang; et al. Field Crops Research 2025. doi:10.1016/j.fcr.2025.110032

Other claims from this paper (6)
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 resultmeasured

Claim · model-written summary

Errors attributable to the model are of similar magnitude to conventional pasture yield measurement errors

Outcome
Errors attributable to the modele0
Comparator
conventional pasture yield measurementse0

Verbatim

e0

“Errors attributable to the model are of a similar magnitude to those of conventional pasture yield measurements”

✓ located verbatim in the source · abstract, characters 1205–1316

Title

Loss in monthly pasture production resulting from dryland conditions in the Waikato

K.J. McAneney; M.J. Judd; W.C. Weeda New Zealand Journal of Agricultural Research 1982. doi:10.1080/00288233.1982.10420904

Other claims from this paper (4)
Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

For many whitefly detection models, most errors were species classification errors.

Outcome
most errors occurred in species classificatione0
Comparator
many modelse0

Verbatim

e0

“While, for many models, most errors occurred in species classification, those trained on low-resolution images had a higher proportion of localization errors.”

✓ located verbatim in the source · abstract, characters 853–1011
t0

“tomato leaflets”

✓ located verbatim in the source · title, characters 98–113

Title

Effect of image resolution on automatic detection of whitefly (Hemiptera: Aleyrodidae) species on tomato leaflets using deep learning

Mikio Kamei Smart Agricultural Technology 2023. doi:10.1016/j.atech.2023.100372

Other claims from this paper (7)
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)

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