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Record W7117302418 · doi:10.71318/apom.2013.67.4.186

Performance of Sweet Cherry Rootstocks in the 1998NC-140 Regional Trial in Western North America

2013· article· W7117302418 on OpenAlexfundaboutno aff
Frank Kappel, Greg Lang, Anita N. Azarenko, T. J. Facteau, Al Gaus, Ron Godin, T. Lindstrom, R. Núñez-Elisea, R. R. Pokharel, Matthew Whiting, C.R. Hampson

Bibliographic record

VenueJournal of American Pomological Society · 2013
Typearticle
Language
FieldAgricultural and Biological Sciences
TopicPlant Physiology and Cultivation Studies
Canadian institutionsnot available
FundersAgriculture and Agri-Food CanadaWashington Tree Fruit Research CommissionUtah Agricultural Experiment Station
KeywordsRootstockCultivarSeedlingPrunusYield (engineering)

Abstract

fetched live from OpenAlex

A regional trial evaluating the performance of rootstocks for sweet cherries in western North America was planted in the spring of 1998 at six locations in the states of Washington, Oregon, Colorado, and Utah, and in the province of British Columbia, Canada. The rootstocks included: Mazzard seedling ( Prunus avium), P. mahalebseedling, Gisela® (G) 3, G5, G6, G7, Giessen (Gi) 195/20, Gi 318/17, Gi 473/10, Tabel® Edabriz, Weiroot (W) 10, W13, W72, W53, W154, and W158. The scion cultivar was 'Bing'. Rootstocks significantly affected tree size, yield and fruit quality, and these effects were not consistent across all locations. However, Mazzard and Mahaleb consistently produced among the largest trees and W72, G3 and W53 among the smallest. Root suckers tended to be most numerous for Tabel® Edabriz and the Weiroot series. Mazzard and Mahaleb usually had the lowest yield and yield efficiency. G3, G5, G7, W53 and W72 were fivefold or more as yield-efficient as Mazzard.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score0.679

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.250
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2013
Admission routes2
Has abstractyes

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