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Record W1976404078 · doi:10.3109/07388551.2010.513327

Bio-encapsulation of microbial cells for targeted agricultural delivery

2010· review· en· W1976404078 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

VenueCritical Reviews in Biotechnology · 2010
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicLegume Nitrogen Fixing Symbiosis
Canadian institutionsAgriculture and Agri-Food CanadaInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsBiotechnologyBiochemical engineeringContext (archaeology)Microbial inoculantAgricultureBiofertilizerBiologyEngineeringAgronomyBacteriaEcology

Abstract

fetched live from OpenAlex

Biofertilizers, namely Rhizobium and biocontrol agents such as Pseudomonas and Trichoderma have been well established in the field of agricultural practices for many decades. Nevertheless, research is still going on in the field of inoculant production to find methods to improve advanced formulation and application in fields. Conventionally used solid and liquid formulations encompass several problems with respect to the low viability of microorganisms during storage and field application. There is also lack of knowledge regarding the best carrier in conventional formulations. Immobilization of microorganisms however improves their shelf-life and field efficacy. In this context, microencapsulation is an advanced technology which has the possibility to overcome the drawbacks of other formulations, results in extended shelf-life, and controlled microbial release from formulations enhancing their application efficacy. This review discusses different microencapsulation technologies including the production strategies and application thereof in agricultural practices.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch 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 score0.976
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0030.001
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 head0.299
Teacher spread0.260 · 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