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Record W7054887319

Carbon and Nitrogen Dynamics in Plants Grown at Low CO2 Conditions of the Past

2019· article· en· W7054887319 on OpenAlexfundno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2019
Typearticle
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsCarbon fibersNitrogenElymusNutrientGrowing seasonCarbon dioxideCarbon cycleIsotopes of carbon
DOInot available

Abstract

fetched live from OpenAlex

For most of the recent evolutionary history of plants, atmospheric CO2 concentrations have been far below modern values. However, little is known about how plants grown in a low CO2 environment balance their carbon demand for growth while meeting their requirement for nitrogen acquisition, the establishment of mycorrhizal fungal associations, and the production of defense compounds. Here, I investigated how low CO2 affects Elymus canadensis and Picea mariana by comparing their growth at low and current CO2 concentrations. I found that reduced N availability exacerbated low CO2 effects on growth, and reduced stomatal index and N isotope composition, indicating that the use of these variables as paleo-indicators can be influenced by N availability. Mycorrhizal association was enhanced in low-CO2 plants, and increased root N but decreased root δ15N, which could skew the interpretation of δ15N when comparing non- and mycorrhizal ancient plant samples. Growth at low CO2 decreased the formation and size of resin ducts and terpene production, suggesting that plants growing at past CO2 conditions had reduced capacity to chemically defend against herbivory.

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 score0.002
Threshold uncertainty score0.553

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 head0.025
GPT teacher head0.233
Teacher spread0.208 · 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
Published2019
Admission routes1
Has abstractyes

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