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Record W2382600850

The Screening and Identification of Transgenic Goat Fibroblast Cells with Sweet Protein Brazzein Gene

2014· article· en· W2382600850 on OpenAlexaff
Wang Chun-shen

Bibliographic record

VenueAnhui nongye kexue · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Genetics and Reproduction
Canadian institutionsScience North
Fundersnot available
KeywordsTransgeneTransfectionMolecular biologyBiologyFibroblastCellGenetically modified mouseCell cultureGreen fluorescent proteinGeneExpression vectorCationic liposomeRecombinant DNABiochemistryGenetics
DOInot available

Abstract

fetched live from OpenAlex

[Objective]In order to obtain transgenic goat fibroblast cells with sweet protein Brazzein gene. [Method]Goat fibroblast cells were transfected with mammary gland specific expression vector STP-pBC1 constructed in the previous work by cationic liposome method and cultured G418-resistant cell. After PCR identified,transgenic cell line with Tem was established. The G418 positive cells were detected. [Result]Transgenic cell could be obtained by the optimum concentration of G418. Morphology of the transgenic cell and transgenic cells after freezing-thawing was similar with normal mammary epithelial cells,the cell growth curve wasSshape,PCR results showed that the vector constructed was integrated into genome. [Conclusion]The transgenic cells with temporin-GFP were filtrated,and lay the foundation for the transgenic goat with expression temporin in mammary.

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 score0.002
Threshold uncertainty score0.005

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)0.0020.001

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
Published2014
Admission routes1
Has abstractyes

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