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Record W1604554747 · doi:10.1002/9780470054581.eib269

Energy Metabolism of Cells Used for Industrial Production

2010· other· en· W1604554747 on OpenAlexaff
Michael Butler, Richard Sparling, Deborah A. Court

Bibliographic record

VenueEncyclopedia of Industrial Biotechnology · 2010
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Metabolic Engineering and Bioproduction
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsCatabolismIndustrial microbiologyFermentationMetabolic engineeringBiochemistryMetabolic pathwayBiochemical engineeringChemistryMetabolismBiologyBiotechnologyEnzyme

Abstract

fetched live from OpenAlex

Abstract The metabolic pathways of bacterial, fungal and animal cells used in industrial bioprocesses are described. Some of the pathways of catabolism utilizing carbohydrates such as glucose for energy and reducing equivalents are common to many of these cells. Cells used in industrial processes are commonly selected or genetically engineered to allow the synthesis of specific products required in large quantities. Some of these products are the end‐points of catabolic pathways and include ethanol, acetate and lactate. Secondary metabolites have been the source of many pharmaceutical products such as antibiotics, which are produced from fungal fermentation. Animal cells in culture have been the basis of bioprocesses used to produce recombinant glycoproteins many of which are developed as novel biopharmaceuticals. These cultures require careful design of culture conditions to maximize cell growth and productivity.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.003

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 head0.011
GPT teacher head0.215
Teacher spread0.204 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2010
Admission routes1
Has abstractyes

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