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Record W7009858762

Factors affecting Winter Survival of Dactylis glomerata in Alberta, Canada

2024· article· en· W7009858762 on OpenAlexaboutno aff

Bibliographic record

VenueUKnowledge (University of Kentucky) · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPasture and Agricultural Systems
Canadian institutionsnot available
Fundersnot available
KeywordsDactylis glomerataSnowTiller (botany)GrazingWinter wheatBromus
DOInot available

Abstract

fetched live from OpenAlex

Dactylis glomerata (orchardgrass) is not completely winter hardy under the extreme continental climate of the Canadian prairies. It grows vigorously in the autumn, but cutting or grazing at this time may affect its winter survival. Miniature snow fences (30 cm) were used to examine the interaction between autumn harvest date and stubble height effects on winter survival and subsequent yields. Plants cut in September and October had lower autumn carbohydrate storage levels and, in the absence of a snow fence, suffered more winter kill and had lower spring yields than plants cut in August. The presence of a snow fence encouraged snow trapping which insulated the tiller species from the extreme winter temperatures and reduced the cutting date effects. Thus autumn cutting' date appears to influence winter survival of orchardgrass more through its effect on the snow-trapping ability of the stubble than through its effect on storage carbohydrated levels.

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)0.000
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 score0.348
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.018
GPT teacher head0.186
Teacher spread0.168 · 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
Published2024
Admission routes1
Has abstractyes

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