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Record W2354159399

Alleviation Effects of Different Organic Acids on Induction and Growth of Rice(Oryza Sativa L.) Callus under Cu~(2+) Stress

2009· article· en· W2354159399 on OpenAlexvenueno aff
Yishan Cai

Bibliographic record

VenueSeed · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Growth and Agriculture Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsCallusAscorbic acidOryza sativaOxalic acidBrowningCitric acidChemistryOrganic acidHorticultureBotanyFood scienceBiochemistryBiology
DOInot available

Abstract

fetched live from OpenAlex

Using rice seed as material to study the alleviation effects of different organic acids on induction and growth of rice callus under oxidative stress induced by Cu2+.The result showed that different Cu2+ concentration in the MS culture medium inhibited evidently induction and growth of rice callus,and inhibitory effect increased with Cu2+ increasing.When Cu2+ concentration up to 1 000 μmol/L,the callus was small relatively,and its surface was hard and dry.Added organic acid,such as ascorbic acid and citric acid and oxalic acid,could improve significantly callus growth on condition that Cu2+ stress,especially with 250 μmol/L ascorbic acid was the best,the callus was fresh,light yellow,loose,the surface moist,close to controlled.Meanwhile,browning phenomenon was inhibited by ascorbic acid more effectively than the other two acids.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.630
Threshold uncertainty score0.148

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 head0.007
GPT teacher head0.190
Teacher spread0.183 · 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
Published2009
Admission routes1
Has abstractyes

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