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Record W2330973006 · doi:10.2134/agronj2013.0195

Timothy Yield and Nutritive Value under Climate Change in Canada

2013· article· en· W2330973006 on OpenAlexafffundabout
Qi Jing, Gilles Bélanger, Budong Qian, V. S. Baron

Bibliographic record

VenueAgronomy Journal · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicClimate change impacts on agriculture
Canadian institutionsAlberta Crop Industry Development FundAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food Canada
KeywordsDry matterNeutral Detergent FiberForageAnimal scienceYield (engineering)AgronomyGrowing seasonPhleumBiology

Abstract

fetched live from OpenAlex

Timothy ( Phleum pratense L.) is a dominant forage grass in Canada but its performance under projected future climate conditions has not been evaluated. This study combined the grass model CATIMO (Canadian Timothy Model) with baseline (1961–1990) and projected future (2040–2069) climate scenarios to assess the response of timothy to climate change at 10 sites across Canada. Projected future conditions are expected to have the following effects on timothy: (i) earlier growth onset (10‐site average: –21 d; range: –4 to –40 d), date of first harvest (–15 d; –11 to –25 d), and date of second harvest (–20 d; –17 to –29 d), along with a later end to the growing season (+12 d; 0 to +18 d); (ii) increased dry matter (DM) yield at first harvest (+355 kg ha –1 ; –917 to +826 kg ha –1 ) but decreased DM yield at second harvest (–427 kg ha –1 ; +47 to –936 kg ha –1 ); (iii) increased neutral detergent fiber (NDF) concentration at first harvest (+22 g kg –1 DM; –22 to +94 g kg –1 DM) but a small decrease (–3 g kg –1 DM; +7 to –30 g kg –1 DM) at second harvest; and (iv) decreased NDF digestibility at first harvest (–6 g kg –1 NDF; +7 to –30 g kg –1 NDF) and second harvest (–23 g kg –1 NDF; –11 to –35 g kg –1 NDF). The longer growing season (+581°C‐d to +1219°C‐d) is expected to result in an additional harvest by 2040 to 2069.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.303
Threshold uncertainty score0.999

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)0.0020.000

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 head0.214
Teacher spread0.180 · 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.

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

Citations28
Published2013
Admission routes3
Has abstractyes

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