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Record W4365445796 · doi:10.1139/cjps-2022-0121

Redcliff hard red spring wheat

2023· article· en· W4365445796 on OpenAlexafffundvenueabout
Muhammad Iqbal, Dean Spaner, Izabela Ciechanowska, Klaus Strenzke, Brian L. Beres

Bibliographic record

VenueCanadian Journal of Plant Science · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWheat and Barley Genetics and Pathology
Canadian institutionsAgriculture and Agri-Food CanadaAgriculture Food and Rural DevelopmentUniversity of Alberta
FundersAlberta Wheat CommissionUniversity of AlbertaWestern Grains Research FoundationNatural Sciences and Engineering Research Council of CanadaAlberta Crop Industry Development Fund
KeywordsStem rustTest weightSpring (device)Rust (programming language)AgronomyBiologyGrain yieldHorticultureFusariumCultivar

Abstract

fetched live from OpenAlex

Redcliff hard red spring wheat was developed at the University of Alberta using a modified bulk breeding method. In 3 years of evaluation in the Parkland Cooperative test from 2018 to 2020, Redcliff produced 7.3% more grain and matured 1.9 days earlier than the highest yielding check Carberry. Redcliff had 3.9 cm taller plants than Carberry but shorter than the other checks and displayed good lodging tolerance. The test weight of Redcliff was slightly higher than Carberry and Parata but lower than Glenn. The grain weight of Redcliff was higher than Parata and similar to the other checks. Grain protein content was within the range of the checks. Redcliff was rated “resistant” to the prevalent races of stem rust, “resistant” to “moderately resistant” to Fusarium head blight, “intermediate” to leaf and stripe rusts, whereas “moderately susceptible” to common bunt. Three years of end-use quality evaluation have indicated that Redcliff is acceptable for the Canada Western Red Spring wheat market class, with improvements in flour yield.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.232

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.210
Teacher spread0.176 · 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 designBench or experimental
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
Published2023
Admission routes4
Has abstractyes

Explore more

Same venueCanadian Journal of Plant Science→Same topicWheat and Barley Genetics and Pathology→French-language works237,207→