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Record W2379129755

Effect of Water Stress on Rice Cultiver Physiology Characteristic

2014· article· en· W2379129755 on OpenAlexvenueno aff
Jiang Zhi-h

Bibliographic record

VenueSeed · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRice Cultivation and Yield Improvement
Canadian institutionsnot available
Fundersnot available
KeywordsPoint of deliveryMalondialdehydeSuperoxide dismutasePhotosynthesisWater stressJaponica ricePeroxidaseStress (linguistics)HorticultureChemistryBiologyJaponicaBotanyOxidative stressEnzymeBiochemistry
DOInot available

Abstract

fetched live from OpenAlex

In this experiment,we take materials from fine-quality japonica hybrid rice dianza 31,using pot experiment,setting up five water stress treatment at booting stage,carrying out different degrees of water stress, through measuring the changes of the blade of photosynthetic characteristics,leaf and root's malondialdehyde( MDA) concentration,peroxidase( POD) activity,superoxide dismutase( SOD) activity after water stress treatment and studied the effect of water stress on dianza 31 at booting stage physiological characteristics. The results show that,with the increase of water stress,booting stage dianza 31 agronomic characters,photosynthetic characteristics marked descend,leaf and root's MDA concentration,POD activity,SOD activity increased.

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 score0.525
Threshold uncertainty score0.221

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 head0.008
GPT teacher head0.214
Teacher spread0.205 · 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
Published2014
Admission routes1
Has abstractyes

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