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Record W4414851385 · doi:10.3390/plants14193070

Development and Application of an In Vitro Pollen Viability Assay for Comparative Safety Assessment of Transgenic Alfalfa (Medicago sativa L.)

2025· article· en· W4414851385 on OpenAlexaff
Yuxiao Chen, Xiaochun Zhang, Jiangtao Yang, Diandian Guo, Xujing Wang, Zhixing Wang

Bibliographic record

VenuePlants · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetically Modified Organisms Research
Canadian institutionsBiotechnology Research Institute
FundersChinese Academy of Agricultural Sciences
KeywordsPollenBiosafetyGenetically modified cropsTransgeneForageGenetically modified organismGenetically modified maize

Abstract

fetched live from OpenAlex

Alfalfa (Medicago sativa L.) is a vital global forage crop. Transgenic technology promises enhanced yield and quality, but requires rigorous environmental risk assessment, particularly regarding pollen-mediated gene flow, for which standardized protocols are lacking. Based on an optimized in vitro culture medium, this study developed a method to assess alfalfa pollen viability. Using a single-factor experimental design, key assessment parameters were established at 1/4/8 h and 20/30/40 °C. A comparative analysis revealed no significant difference (p > 0.05) in pollen viability between the transgenic line SA6-8 and its non-transgenic parent “ZM-1” within this evaluation system. This result indicates that the genetic modification did not impact the pollen viability of SA6-8. By establishing this in vitro germination-based pollen viability assessment system and comparatively analyzing pollen viability between transgenic alfalfa and its non-transgenic parent under diverse environmental conditions, our approach provides crucial insights for optimizing transgenic alfalfa planting strategies and strengthening biosafety review protocols.

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 score0.666
Threshold uncertainty score0.122

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 head0.038
GPT teacher head0.324
Teacher spread0.287 · 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
Published2025
Admission routes1
Has abstractyes

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