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Record W2381240828

Study on Optimizing the Accelerated Ageing Condition of Alfalfa Seeds

2010· article· en· W2381240828 on OpenAlexvenueno aff
Yinfei Li

Bibliographic record

VenueSeed · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSeed Germination and Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsAgeingGerminationAccelerated agingHorticultureBiologyHealthy ageingMaterials scienceComposite material
DOInot available

Abstract

fetched live from OpenAlex

Three samples of alfalfa(Medicago sative L)seeds with different germination level were used in the experiment and conducted to analyse the effect of the aging temperature(39,41,43,45℃)and aging duration(24,36,48,60,72,84,96h)on the germination percentage,and to find out the suitable condition and procedure for the accelerated aging test of alfalfa seed.The results showed that the germination rate decreased gradually with the ageing temperature increasing,and germination rate after ageing was decreased significantly(p0.05)at 45℃.The seed germination of Lot1,Lot2 and Lot3 gradually decreased with the ageing duration prolonging,but there were not significant differen(p0.05)from ageing duration 36h to 84h.Although ageing temperature could promote the seed ageing,the germination rate after ageing of Lot1 seeds with higher germination percentage changed slowly within ageing duration 84h,and that of Lot3 with lower germination percentage changed quickly beyond ageing 36h.The interaction between the ageing temperature and duration was significantly related(p0.01)with the germination rate after ageing of alfalfa seed,ageing temperature and duration were all the key factor for promoting the seed ageing.The result indicated that ageing temperature 45℃ and ageing duration 84h was suitable condition for accelerated ageing test of alfalfa seed.

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 score0.976
Threshold uncertainty score0.213

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 head0.040
GPT teacher head0.281
Teacher spread0.241 · 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
Published2010
Admission routes1
Has abstractyes

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