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Record W4251089607 · doi:10.32920/ryerson.14664516.v1

Nutritional change due to climate warming: an analysis of fatty acid content of pasture plants common to Southern Ontario

2021· preprint· en· W4251089607 on OpenAlexaffabout

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPastureFatty acidPolyunsaturated fatty acidGlobal warmingClimate changeGrasslandEcosystemAgronomyEnvironmental scienceChemistryEcologyBiologyBiochemistry

Abstract

fetched live from OpenAlex

Climate change will produce a wide range of challenges for grassland ecosystems, including increased global surface air temperature. Increased temperature can increase cell membrane fluidity in plants and other organisms; a response known as homeoviscous adaptation. However, this phenomenon has not been extensively studied in grassland plant species and has not been widely observed in plants from a climate warming perspective. I exposed seven species of agricultural forage plants to a temperature gradient consistent with climate change estimates for Southern Ontario. I compared relative fatty acid composition between temperature conditions, paying particular attention to the relative content of saturated, monounsaturated, and polyunsaturated fatty acids, and essential fatty acids. For most species, I found saturated fatty acid content decreased with increasing temperature, while polyunsaturated fatty acid content and essential fatty acid content increased with increasing temperature. My thesis provides insights into the effects of climate warming on pasture ecosystems.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.501
Threshold uncertainty score0.992

Distilled classifier scores by category (both heads)

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

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 head0.101
GPT teacher head0.275
Teacher spread0.175 · 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

Citations1
Published2021
Admission routes2
Has abstractyes

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