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Record W4366089810 · doi:10.3390/biology12040601

Biotechnologically Engineered Plants

2023· review· en· W4366089810 on OpenAlexaff
Zareen Narayanan, Bernard R. Glick

Bibliographic record

VenueBiology · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicTransgenic Plants and Applications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBiologyCommercializationBiotechnologyGenetically modified cropsPipeline (software)Biochemical engineeringTransgeneGeneEngineeringGeneticsBusiness

Abstract

fetched live from OpenAlex

The development of recombinant DNA technology during the past thirty years has enabled scientists to isolate, characterize, and manipulate a myriad of different animal, bacterial, and plant genes. This has, in turn, led to the commercialization of hundreds of useful products that have significantly improved human health and well-being. Commercially, these products have been mostly produced in bacterial, fungal, or animal cells grown in culture. More recently, scientists have begun to develop a wide range of transgenic plants that produce numerous useful compounds. The perceived advantage of producing foreign compounds in plants is that compared to other methods of producing these compounds, plants seemingly provide a much less expensive means of production. A few plant-produced compounds are already commercially available; however, many more are in the production pipeline.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score0.861

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.072
GPT teacher head0.347
Teacher spread0.275 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations10
Published2023
Admission routes1
Has abstractyes

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