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Method / resourceobservedoriginal resultbasis n/a

Claim · model-written summary

Dividing multiple-regression coefficients by R yields the partial regression coefficients of the yield-estimating equation.

Outcome
Partial regression coefficientse0
Comparator
coefficients of a multiple regression equatione0

Verbatim

e0

“Partial regression coefficients of this equation are obtained by dividing the corresponding coefficients of a multiple regression equation by the coefficient of multiple correlation, R.”

✓ located verbatim in the source · abstract, characters 274–459
t0

“Wheat Yields”

✓ located verbatim in the source · title, characters 74–86

Title

A Mathematical Procedure for Evaluating Relationships Between Climate and Wheat Yields1

Wendell C. Johnson Agronomy Journal 1959. doi:10.2134/agronj1959.00021962005100110001x

Observationobservedoriginal resultmeasured

Claim · model-written summary

Regression coefficients varied between sampling dates.

Outcome
regression coefficientse0
Direction
variede0

Verbatim

e0

“the regression coefficients varied between sampling dates”

✓ located verbatim in the source · abstract, characters 472–529
t0

“corn”

✓ located verbatim in the source · title, characters 56–60

Title

Chlorophyll meter evaluation for nitrogen management in corn

D. Smeal; H. Zhang Communications in Soil Science and Plant Analysis 1994. doi:10.1080/00103629409369130

Other claims from this paper (6)
Associationobservedoriginal resultsignificant (as stated)measured

Claim · model-written summary

Regression coefficients correlated significantly and positively only with coefficients of variation.

Taxon
soybean cultivarsGlycine maxt0
Outcome
Regression coefficientse0
Direction
positively correlatede0
Comparator
coefficients of variatione0

Verbatim

e0

“Regression coefficients were significantly and positively correlated only with coefficients of variation”

✓ located verbatim in the source · abstract, characters 458–562
t0

“soybean cultivars”

✓ located verbatim in the source · title, characters 14–31

Title

Evaluation of soybean cultivars using parametric and nonparametric stability estimates

G. L. Yue; K. L. Roozeboom; W. T. Schapaugh; et al. Plant Breeding 1997. doi:10.1111/j.1439-0523.1997.tb00995.x

Other claims from this paper (6)
Observationobservedoriginal resultnot significant (as stated)measured

Claim · model-written summary

The three site-specific regression coefficients did not differ significantly.

Outcome
regression coefficientse0

Not reportedDirection

Verbatim

e0

“These regression coefficients are not significantly different.”

✓ located verbatim in the source · abstract, characters 794–856
t0

“BARLEY”

✓ located verbatim in the source · title, characters 35–41

Title

RELATION OF LOOSE SMUT TO YIELD OF BARLEY

Wm. Semeniuk; J. G. Ross Canadian Journal of Research/Canadian journal of research 1942. doi:10.1139/cjr42c-041

Other claims from this paper (9)
Observationobservedoriginal resultsignificant (as stated)measured

Claim · model-written summary

Regression coefficients differed significantly among cultivars within each experiment.

Taxon
cultivarse0
Outcome
regression coefficientse0

Verbatim

e0

“There were also significant differences in regression coefficients among cultivars in each experiment.”

✓ located verbatim in the source · abstract, characters 362–464

Title

Evaluation of Muskmelon Cultivar Performance by Joint Regression Analysis1

Timothy J Ng; C. A. McClurg; F. F. Angell; et al. Journal of the American Society for Horticultural Science 1980. doi:10.21273/jashs.105.2.220

Other claims from this paper (6)
Associationobservedoriginal resultmeasured

Claim · model-written summary

Low regression deviations tended to occur with regression coefficients below 1.0.

Taxon
soybeanGlycine maxt0
Outcome
deviations from regressione0
Value
below 1.0e0
Comparator
regression coefficientse0

Not reportedDirection

Verbatim

e0

“Low deviations from regression tended to be associated with regression coefficients below 1.0.”

✓ located verbatim in the source · abstract, characters 338–432
t0

“Soybean Populations”

✓ located verbatim in the source · title, characters 24–43
t1

“Soybean Populations”

✓ located verbatim in the source · title, characters 24–43
e1

“Low deviations from regression tended to be associated with regression coefficients below 1.0.”

✓ located verbatim in the source · abstract, characters 338–432

Title

Phenotypic Stability in Soybean Populations1

R. R. Smith; D. E. Byth; B. E. Caldwell; et al. Crop Science 1967. doi:10.2135/cropsci1967.0011183x000700060011x

Other claims from this paper (3)
Observationobservedoriginal resultno effectmeasured

Claim · model-written summary

Regression coefficients did not differ between seasons.

Outcome
regression coefficientse0
Direction
did not differe0
Comparator
seasonse0

Verbatim

e0

“The regression coefficients did not differ among seasons”

✓ located verbatim in the source · abstract, characters 883–939
t0

“broccoli”

✓ located verbatim in the source · title, characters 31–39

Title

A petiole sap nitrate test for broccoli

Aki Kubota; Thomas L. Thompson; Thomas A. Doerge; et al. Journal of Plant Nutrition 1997. doi:10.1080/01904169709365285

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

Claim · model-written summary

Multiple regression produced higher correlation coefficients.

Outcome
correlation coefficientse0
Direction
highere0
Comparator
multiple regression analysise0

Not reportedTaxon

Verbatim

e0

“Corresponding multiple regression analysis resulted in higher correlation coefficients”

✓ located verbatim in the source · abstract, characters 727–813

Title

Estimation of old field ecosystem biomass using low altitude imagery

Salleh Mohd. Nor; Gene R. Safir; T.M. Burton; et al. NASA Technical Reports Server (NASA) 1977

Other claims from this paper (2)
Observationobservedoriginal resultno effectnot significant (as stated)measured

Claim · model-written summary

Regression coefficients for mowing and biomass did not differ between the two regression lines in either experiment.

Taxon
Cirsium arvenseCirsium arvenset0
Outcome
regression coefficientse0
Direction
no differencee0

Verbatim

e0

“in both experiments there was no difference between the regression coefficients”

✓ located verbatim in the source · abstract, characters 746–825
t0

“Cirsium arvense”

✓ located verbatim in the source · title, characters 22–37

Title

Mechanical control of Cirsium arvense in organic farming

Enrico Graglia; Bo Melander Organic Eprints (International Centre for Research in Organic Food Systems, and Research Institute of Organic Agriculture) 2005

Other claims from this paper (4)
Recommendationauthor interpretationoriginal resultbasis n/a

Claim · model-written summary

A regression approach for forage uNDF requires specific equations and different regression coefficients for each forage type.

Taxon
forage typee1
Outcome
specific equations and different regression coefficientse1

Verbatim

e1

“In conclusion, a regression approach requires specific equations and different regression coefficients for each forage type”

✓ located verbatim in the source · abstract, characters 1802–1925

Title

Estimation of the indigestible fiber in different forage types

A. Palmonari; A. Gallo; M. Fustini; et al. Journal of Animal Science 2015. doi:10.2527/jas.2015-9649

Other claims from this paper (12)

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