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Record W4254944612 · doi:10.33140/eesrr.03.03.13

Is Diminishing Solar Activity Detrimental to Canadian Prairie Agriculture?

2020· article· en· W4254944612 on OpenAlexaboutno aff

Bibliographic record

VenueEarth & Environmental Science Research & Reviews · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicClimate change impacts on agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsPrecipitationEnvironmental scienceGrowing degree-dayPacific decadal oscillationCanolaClimate changeArctic foxAtmospheric sciencesGrowing seasonArcticClimatologyEl Niño Southern OscillationAgronomyPhenologyGeographyMeteorologyGeologyOceanographyBiology

Abstract

fetched live from OpenAlex

During the grain growing months of May-July, the mean temperature on the Canadian prairies has cooled down by 2ºC in the last 30 years. The cooling appears to be most certainly linked to diminishing solar activity as the Sun approaches a Grand Solar Minimum in the next decade or so. This cooling has led to a reduction in Growing Degree Days (GDDs) and has also impacted the precipitation pattern. The GDDs in conjunction with mean temperature and precipitation are important parameters for the growth of various grains (wheat, barley, canola etc.) on the prairies. In this study, we investigate the impact of declining GDDs and associated temperature and precipitation patterns on Prairie grain yields and quality. Our analysis shows that there has been a loss of about 100 GDDs over the time frame of 1985-2019. The loss in GDDs is also linked to some of the large-scale Atmosphere-Ocean parameters like the Pacific Decadal Oscillation (PDO), North Pacific Index (NPI) and Arctic Oscillation (AO). Our analysis suggests grain yield and quality could be significantly impacted in the coming years as solar activity continues to diminish.

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)0.003
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 score0.020
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.172
GPT teacher head0.348
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 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
Published2020
Admission routes1
Has abstractyes

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