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Record W2387010446

Allelopathic Effects of Aqueous Extracts of Eupatorium adenophorum Spreng. by Different Treatment Methods on Seedling Growth of Pinus Yunanensis Franch

2012· article· en· W2387010446 on OpenAlexvenueno aff
Yang Gui-ying

Bibliographic record

VenueSeed · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAllelopathy and phytotoxic interactions
Canadian institutionsnot available
Fundersnot available
KeywordsAllelopathySeedlingEupatoriumGerminationHorticultureBotanyBiologyAqueous extractTraditional medicineMedicine
DOInot available

Abstract

fetched live from OpenAlex

In order to know the influence of sample treatment methods on Allelopathy intensity,Pinus yunnanensis Seeds were treated by aqueous extracts of Eupatorium adenophorum above-ground of EEDS(the sample which eliminated enzyme and dried by heat) and CFS(the crumbled fresh sample) and IFS(the integrity fresh sample),observed the influence on seedling growth after seed germination.The result showed that the allelopathic effects of the extracts of E.adenophorum of different treatments on seedling growth of Pinus yunnanensis were different.On the whole,at the concentration of 0.04 g/mL,the aqueous extract of different treatments had a significant inhibitory effect on seedling growth of P.yunnanensis,inhibitory effects of EEDS and CFS were stronger than IFS's,the mean differences between IFS and CFS were significant at the 0.01 level.The mean differences between IFS and EEDS were also significant at the 0.01 level.The inhibitory effects of different treatments got weaker with the concentration decreasing,and even turned into a stimulating effect,the critical concentration of IFS which stimulated seedling growth was higher than that of EEDS and CFS,The function form and degree of allelopathy were bound up with sample treatment means,so,the integrity fresh sample was the first choose when extracting allelopathic chemicals.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.242
Threshold uncertainty score0.343

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 head0.015
GPT teacher head0.260
Teacher spread0.245 · 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 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
Published2012
Admission routes1
Has abstractyes

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