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Record W2076528606 · doi:10.4141/p05-001

Oat quality and yield as affected by kernel moisture at swathing

2005· article· en· W2076528606 on OpenAlex
William E. May, Ramona M. Mohr, G. P. Lafond, F. Craig Stevenson

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of Plant Science · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Plant Science, Crop Management
Canadian institutionsUniversity of SaskatchewanAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaMinistry of Agriculture - Saskatchewan
KeywordsAvenaTest weightYield (engineering)Water contentAgronomyMoistureMathematicsKernel (algebra)GerminationHorticultureBiologyCultivarChemistryMaterials scienceEngineering

Abstract

fetched live from OpenAlex

Increased demand for high-quality oat has rekindled interest in improving oat (Avena sativa L.) yield and quality by managing the timing of oat swathing. The objective of this study was to determine the effect of swathing at five levels of kernel moisture on yield and seed quality at Indian Head, SK, and Brandon, MB, from 1997 (Indian Head only) to 2000. The largest benefit to yield and quality was achieved when swathing was delayed from 50 to 41% kernel moisture. Kernel weight, plump seed and groat yield were optimized when kernel moisture was between 36 and 30% moisture content. Dockage, protein content and oil content also improved with later swathing dates. Swathing should not begin until a kernel moisture content of 41% has been reached. After 30% kernel moisture was reached, no improvement in oat yield and quality occurred when swathing was delayed any further. Key words: Avena sativa L., test weight, thin seed, groat yield, protein, germination

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.828
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.215
Teacher spread0.196 · 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