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Record W4225156228 · doi:10.3390/polym14091806

Carbohydrate-Binding Modules of Potential Resources: Occurrence in Nature, Function, and Application in Fiber Recognition and Treatment

2022· review· en· W4225156228 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

VenuePolymers · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnzyme Production and Characterization
Canadian institutionsUniversity of New Brunswick
FundersNational Natural Science Foundation of China
KeywordsCarbohydrate-binding moduleFunction (biology)Domain (mathematical analysis)Substrate (aquarium)Molecular recognitionBiochemical engineeringFiberComputer scienceGlycoside hydrolaseMaterials scienceChemistryBiochemistryBiologyEngineeringMathematicsEnzymeCell biologyOrganic chemistryMoleculeComposite material

Abstract

fetched live from OpenAlex

Great interests have recently been aroused in the independent associative domain of glycoside hydrolases that utilize insoluble polysaccharides-carbohydrate-binding module (CBM), which responds to binding while the catalytic domain reacts with the substrate. In this mini-review, we first provide a brief introduction on CBM and its subtypes including the classifications, potential sources, structures, and functions. Afterward, the applications of CBMs in substrate recognition based on different types of CBMs have been reviewed. Additionally, the progress of CBMs in paper industry as a new type of environmentally friendly auxiliary agent for fiber treatment is summarized. At last, other applications of CBMs and the future outlook have prospected. Due to the specificity in substrate recognition and diversity in structures, CBM can be a prosperous and promising 'tool' for wood and fiber processing in the future.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.995
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.021
GPT teacher head0.265
Teacher spread0.244 · 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