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Record W3087084396 · doi:10.3390/md18090471

Sea Cucumber Derived Type I Collagen: A Comprehensive Review

2020· review· en· W3087084396 on OpenAlexafffund
Tharindu R. L. Senadheera, Deepika Dave, Fereidoon Shahidi

Bibliographic record

VenueMarine Drugs · 2020
Typereview
Languageen
FieldMaterials Science
TopicCollagen: Extraction and Characterization
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSea cucumberMarine invertebratesScope (computer science)Type I collagenBiologyBiochemistryChemistryEcologyComputer science

Abstract

fetched live from OpenAlex

Collagen is the major fibrillar protein in most living organisms. Among the different types of collagen, type I collagen is the most abundant one in tissues of marine invertebrates. Due to the health-related risk factors and religious constraints, use of mammalian derived collagen has been limited. This triggers the search for alternative sources of collagen for both food and non-food applications. In this regard, numerous studies have been conducted on maximizing the utilization of seafood processing by-products and address the need for collagen. However, less attention has been given to marine invertebrates and their by-products. The present review has focused on identifying sea cucumber as a potential source of collagen and discusses the general scope of collagen extraction, isolation, characterization, and physicochemical properties along with opportunities and challenges for utilizing marine-derived collagen.

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: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.043
GPT teacher head0.326
Teacher spread0.283 · 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
GenreReview

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

Citations121
Published2020
Admission routes2
Has abstractyes

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