MétaCan
Menu
Back to cohort
Record W2380269369

Study on the Dynamics of Endogenous Hormones at Seed Development of Six Grasses

2007· article· en· W2380269369 on OpenAlexvenueno aff
Yi Jin

Bibliographic record

VenueSeed · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsRhizomeEndogenyHormoneBiologyBotanyChemistryEndocrinology
DOInot available

Abstract

fetched live from OpenAlex

4 kinds of endogenous hormones were compared in the seed development of the six species of rhizomatous grasses.The results showed that there were significantly differences in endogenous hormones of appearing time and contents in seed development and in species.The peak value of 4 kinds endogenous hormones contents has distinct order in appearing time and has the same law in different grasses.The peak of GA and ABA appeared firstly in 8-14 d,the second was IAA(11-23 d),the last was ZR(11-33 d),The content is different but change law is same in species.The peak value of 4 kinds endogenous hormones contents were different in endogenous hormones and species,the peak value of GA content is the lowest(15-35 ng/g)(FW),then was IAA(35-91 ng/g)(FW),the highest was ZR(104-129 ng/g)(FW),The peak value of ABA content varied with a great scope in 43-113 ng/g(FW).The content of hormones in 6 rhizomatous grasses had significantly difference,and the species with long rhizome were significantly higher than the ones with short rhizome.The change of hormones has the same model in development of the seeds of 6 rhizomatous grasses,which is that the content decreased with the development,and the content of later period were lower than the former ones.The change model of positive hormone is a curve with two peaks,but the passive ones with more peaks.The hormone ratio of positive to passive was also a same change model,increasing with development,and the later content was higher than the former.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.735
Threshold uncertainty score0.098

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 head0.052
GPT teacher head0.248
Teacher spread0.196 · 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
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueSeedSame topicRuminant Nutrition and Digestive PhysiologyFrench-language works237,207