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Record W4399808991 · doi:10.1016/j.copbio.2024.103167

Industrializing methanotrophs and other methylotrophic bacteria: from bioengineering to product recovery

2024· review· en· W4399808991 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

VenueCurrent Opinion in Biotechnology · 2024
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial metabolism and enzyme function
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBacteriaProduct (mathematics)BiologyBiochemical engineeringChemistryEngineeringMathematicsGenetics

Abstract

fetched live from OpenAlex

Microbes that use the single-carbon substrates methanol and methane offer great promise to bioindustry along with substantial environmental benefits. Methanotrophs and other methylotrophs can be engineered and optimized to produce a wide range of products, from biopolymers to biofuels and beyond. While significant limitations remain, including delivery of single-carbon feedstock to bioreactors, efficient growth, and scale-up, these challenges are being addressed and notable improvements have been rapid. Development of expression chassis, use of genome-scale and regulatory models based on omics data, improvements in bioreactor design and operation, and development of green product recovery schemes are enabling the rapid development of single-carbon bioconversion in the industrial space.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
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
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.077
GPT teacher head0.346
Teacher spread0.269 · 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