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Record W2349347565

Evaluation of Drought Resistant and Response of Millet Seed Germination Under Drought Stress

2013· article· en· W2349347565 on OpenAlexvenueno aff
Jie Liu

Bibliographic record

VenueSeed · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLeaf Properties and Growth Measurement
Canadian institutionsnot available
Fundersnot available
KeywordsGerminationAgronomyDrought resistanceDrought stressDrought toleranceBiologySetariaEconomic shortageCropResistance (ecology)Water stressPrecipitationGeography
DOInot available

Abstract

fetched live from OpenAlex

Millet(Setaria italica(L.)Beauv) is excellent drought resisting crop and important to agriculture.But in recent years,with the warming of the global climate,the water is severe shortage,in the cultivation areas,annual precipitation is 250-450 mm,nine years of spring in ten years were drought,In order to select drought resistant varieties to adapt to cultivation on dry land.In this study,the materials were 9 millet materials.The sprout index of drought resisting,vigor index of drought resisting,and relative germination rate,relative germination potential of 9 millet seeds tested under different osmotic potentials(PEG-6000) to evaluate their drought resistance using the fussy subordinate function.The results indicated that Guo 08-25 and Chi 10-321 had relatively the highest and the lowest drought resistance.The average subordinate values of them resistance to drought stress were relatively 0.710 and 0.023.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.919
Threshold uncertainty score0.160

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.044
GPT teacher head0.244
Teacher spread0.200 · 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
Published2013
Admission routes1
Has abstractyes

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