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Do transgenic plants affect rhizobacteria populations?

2008· review· en· W1986131429 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMicrobial Biotechnology · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant tissue culture and regeneration
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsRhizobacteriaRhizosphereBiotechnologyGenetically modified organismBiologyGenetically modified cropsAdaptabilityEcologyTransgeneBacteria

Abstract

fetched live from OpenAlex

Plant genetic manipulation has led to the development of genetically modified plants (GMPs) expressing various traits. Since their first commercial use in 1996, GMPs have been increasingly used, reaching a global cultivating production area of 114.3 million hectares in 2007. The rapid development of agricultural biotechnology and release of GMPs have provided many agronomic and economic benefits, but has also raised concerns over the potential impact these plants might have on the environment. Among these environmental concerns, the unintentional impact that GMPs might have on soil-associated microbes, especially rhizosphere-inhabiting bacteria or rhizobacteria, represents one of the least studied and understood areas. As rhizobacteria are responsible for numerous key functions including nutrient cycling and decomposition, they have been defined as good indicator organisms to assess the general impact that GMPs might have on the soil environment. This minireview summarizes the results of various experiments that have been conducted to date on the impact of GMPs on rhizobacteria. Both biological and technical parameters are discussed and an attempt is made to determine if specific rhizobacterial responses exist for the different categories of GMPs developed to date.

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.

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 categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.909
Threshold uncertainty score1.000

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 integrity0.0030.000
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 head0.039
GPT teacher head0.298
Teacher spread0.259 · 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