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Record W2087900272 · doi:10.1300/j044v10n02_05

Ultrahigh Carbon Dioxide Atmospheres Increase the Growth Rate, Morphogenesis and Naphthodianthrone Levels in St. John's Wort (<i>Hypericum perforatum</i>) Plants

2003· article· en· W2087900272 on OpenAlexaboutno aff
Steven F. Vaughn, Brent Tisserat, Charles L. Cantrell, Mark A. Berhow

Bibliographic record

VenueJournal of Herbs Spices & Medicinal Plants · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicNatural Compound Pharmacology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHypericum perforatumHypericinCarbon dioxideCuttingHorticultureLiterBotanyHyperforinChemistryShootAnimal scienceBiology

Abstract

fetched live from OpenAlex

ABSTRACT The effect of increased levels of carbon dioxide on the growth (fresh weight), morphogenesis (formation of leaves, roots and shoots) and tissue concentrations of the naphthodianthrones (hypericin and pseudohypericin) was determined for St. John's Wort (Hypericum perforatum L.). Plants, started from shoot cuttings in a vermiculite-peat moss mixture within a greenhouse employing natural sunlight, were grown for eight weeks under CO2 levels of 350, 1500, 3000, 10,000 and 30,000 μl CO2/liter atmospheres. Elevated CO2 levels (≥ 1500 μl CO2/liter) significantly increased growth and morphogenesis compared with ambient (350 μl CO2/liter) levels (control). Levels of hypericin were significantly higher at 1500 and 3000 μl CO2/liter than at ambient CO2, while the higher (10,000 and 30,000 μl CO2/liter) CO2 atmospheres caused reductions in levels of both naphthodianthrones in plant tissues. Because of increased plant growth, however, naphthodianthrone yields were significantly increased at elevated CO2 levels as compared with controls.

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)0.001
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 score0.381
Threshold uncertainty score0.406

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.244
Teacher spread0.226 · 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

Citations1
Published2003
Admission routes1
Has abstractyes

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