MétaCan
Menu
Back to cohort
Record W2322228166 · doi:10.1042/bst20150180

Learning from microbial strategies for polysaccharide degradation

2016· review· en· W2322228166 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBiochemical Society Transactions · 2016
Typereview
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsCanada's Michael Smith Genome Sciences CentreUniversity of British Columbia
FundersBiotechnology and Biological Sciences Research CouncilCanadian Institutes of Health Research
KeywordsPolysaccharideLytic cycleBiochemical engineeringHuman healthBiomass (ecology)MonooxygenaseBiologyDegradation (telecommunications)ChemistryBiochemistryEcologyComputer scienceEngineeringMetabolism

Abstract

fetched live from OpenAlex

Complex carbohydrates are ubiquitous in all kingdoms of life. As major components of the plant cell wall they constitute both a rich renewable carbon source for biotechnological transformation into fuels, chemicals and materials, and also form an important energy source as part of a healthy human diet. In both contexts, there has been significant, sustained interest in understanding how microbes transform these substrates. Classical perspectives of microbial polysaccharide degradation are currently being augmented by recent advances in the discovery of lytic polysaccharide monooxygenases (LPMOs) and polysaccharide utilization loci (PULs). Fundamental discoveries in carbohydrate enzymology are both advancing biological understanding, as well as informing applications in industrial biomass conversion and modulation of the human gut microbiota to mediate health benefits.

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 score0.975
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.029
GPT teacher head0.258
Teacher spread0.229 · 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