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Record W7161978700 · doi:10.82308/53214

Effects of elevated carbon dioxide concentration and temperature under contrasted nitrogen fertilization on timothy

2013· dissertation· en· W7161978700 on OpenAlexaboutno aff
Angela Piva

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicPlant responses to elevated CO2
Canadian institutionsnot available
Fundersnot available
KeywordsForageCarbon dioxidePhotosynthesisHuman fertilizationRuminantPerennial plant

Abstract

fetched live from OpenAlex

Predicted future increases in atmospheric CO2 concentration and air temperature may significantly affect, timothy (Phleum pratense L.), a widely grown perennial forage grass across eastern Canada. A study was done to assess the impacts of predicted increases in CO2 concentration and temperature under contrasted N fertilization on timothy growth, photosynthetic rate, nutritive value, and root degradability as it relates to C sequestration potential. Response of timothy biomass, photosynthesis, and nonstructural carbohydrate and fibre concentrations to CO2 and temperature depended on soil N availability. Future timothy production will likely remain unchanged with potential increases in photosynthesis and the nonstructural carbohydrate concentration available for animal consumption. Future conditions may also reduce forage ruminant N supply without affecting either fibre concentration or digestibility. By decreasing root degradability, these conditions could improve the C sequestration potential of timothy.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

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 communication0.0010.000
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 head0.006
GPT teacher head0.197
Teacher spread0.191 · 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 designBench or experimental
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
Published2013
Admission routes1
Has abstractyes

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