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Record W2921978420

Wheat and barley varietal replacement in western Canada

2006· article· en· W2921978420 on OpenAlexaboutno aff
Catherine Nagy, Joseph G. Nagy

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBioenergy crop production and management
Canadian institutionsnot available
Fundersnot available
KeywordsAgronomyAgricultural economicsBiologyEconomics
DOInot available

Abstract

fetched live from OpenAlex

This paper looks at varietal replacement of wheat and barley by province in \nwestern Canada with respect to the rate of varietal replacement and varietal concentration. A varietal replacement index (VRI) is calculated to represent the rate of varietal replacement using Canadian Wheat Board annual variety survey data for the years 1998-99 to 2004-05. It was hypothesized that the province of Manitoba would have the highest rate of varietal replacement followed by Saskatchewan and then by Alberta. This is based on the claim by researchers that, due mainly to higher rainfall and humidity, the incidence of crop disease is greater in that part of the prairies east of a line drawn through Moose Jaw and Melfort Saskatchewan, and therefore farmers change their varieties more often. The VRIs for the three provinces confirm the hypothesis for Canada Western Red Spring (CWRS) wheat and for malting barley varieties. The hypothesis does not hold for Canada Western Amber Durum (CWAD) and Canada Prairie Spring Red (CPSR) wheat but holds for Canada Western Red Winter (CWRW). This was expected given the relative importance of these markets and corresponding research budgets compared to CWRS. However, a relatively high concentration ratio for CWAD was not expected given the importance of the CWAD market and the varietal research budgets devoted to this class of wheat.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.021
Threshold uncertainty score0.154

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.163
Teacher spread0.157 · 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 source (direct Gemma or distilled Codex), 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
Published2006
Admission routes1
Has abstractno

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