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Record W2355341305

Effects of Superabsorbents Containing Montmorillonite and Polysaccharide on Seed Germination Ability of Salvia Splendens

2013· article· en· W2355341305 on OpenAlexvenueno aff
Qiu Zhao-xi

Bibliographic record

VenueSeed · 2013
Typearticle
Languageen
FieldEngineering
TopicPolymer-Based Agricultural Enhancements
Canadian institutionsnot available
Fundersnot available
KeywordsGerminationSeedlingSalviaHorticultureCarboxymethyl celluloseSAGEDry weightBotanyBiologyChemistrySodium
DOInot available

Abstract

fetched live from OpenAlex

A series of environment-friendly superabsorbents containing natural component montmorillonite( MMT) and sodium carboxymethyl cellulose( CMC) were prepared under room temperature characterized by low-energy consumption using orthogonal experiment. The effects of natural products content and synthetic conditions on seed germination and seedling growth index of salvia splendens were investigated. Orthogonal range analysis showed that MMT and CMC has the great influence on seed germination and seedling growth of salvia splendens. The synthesized water-retaining agent could significantly improved the seed germination capacity and promoted the seedlings growth of salvia splendens. After treating the salvia splendens seeds with optimized superabsorbents,their germination rate,germination potential,germination index,vigor index,root length,lateral root number,total root length and total dry weight were 13. 1,4. 5,12. 6,16,4,65,53. 7 and 16. 7 times as great as the untreated seeds,respectively,which was of great significance to improved the seed germination capacity and promote seedlings growth of salvia splendens,providing the experimental basis for the application of superabsorbents containing natural component in seed preservation and seed production.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.004
GPT teacher head0.193
Teacher spread0.189 · 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 source (direct Gemma or distilled Codex), 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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