MétaCan
Menu
Back to cohort
Record W2116189829 · doi:10.1089/ind.2010.6.164

REVIEW: Genome shuffling: A new trend in improved bacterial production of lactic acid

2010· article· en· W2116189829 on OpenAlexaff
Rojan P. John, G.S. Anisha, Ashok Pandey, K. Madhavan Nampoothiri

Bibliographic record

VenueIndustrial Biotechnology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Metabolic Engineering and Bioproduction
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsLactic acidGenomeDNA shufflingBiologyMicroorganismProductivityBiotechnologyShufflingMetabolic engineeringPopulationProduction (economics)Biochemical engineeringComputational biologyGeneticsBacteriaGeneComputer scienceEngineeringDirected evolution

Abstract

fetched live from OpenAlex

Lactic acid is an environment-friendly chemical with a wide range of industrial applications that is the focus of researchers and biotechnologists worldwide. The economic production of lactic acid can be achieved by exploiting various biotechnological techniques. Among these is the improvement of microorganism strains for industrially desirable characteristics such as high yield and productivity of lactic acid and the ability to grow at low pH and to utilize complex agro-industrial wastes. Whole genome shuffling combines the advantages of dissimilar parents by allowing parental DNA shuffling and hence is believed to improve the characteristics of strains controlled by multiple genes. Recursive genomic recombination within a population of fusant microorganisms can generate strains efficiently with an amplified desirable phenotype.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.279
Threshold uncertainty score0.640

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0010.000
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 head0.014
GPT teacher head0.232
Teacher spread0.218 · 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

Citations7
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueIndustrial BiotechnologySame topicMicrobial Metabolic Engineering and BioproductionFrench-language works237,207