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Record W3111906049 · doi:10.3390/ani10122432

Seaweed and Seaweed Bioactives for Mitigation of Enteric Methane: Challenges and Opportunities

2020· review· en· W3111906049 on OpenAlexaff
D. Wade Abbott, Inga Marie Aasen, K. A. Beauchemin, Fredrïk Gröndahl, Robert J. Gruninger, María Hayes, Sharon Huws, D.A. Kenny, S.J. Krizsan, Stuart F. Kirwan, Vibeke Lind, Ulrich Meyer, Mohammad Ramin, Katerina Theodoridou, Dirk von Soosten, Pamela Walsh, Sinéad M. Waters, Xiaohui Xing

Bibliographic record

VenueAnimals · 2020
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicSeaweed-derived Bioactive Compounds
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBromoformSustainable productionAlgaeBiologyBiotechnologyEnvironmental scienceChemistryProduction (economics)Ecology

Abstract

fetched live from OpenAlex

Seaweeds contain a myriad of nutrients and bioactives including proteins, carbohydrates and to a lesser extent lipids as well as small molecules including peptides, saponins, alkaloids and pigments. The bioactive bromoform found in the red seaweed Asparagopsis taxiformis has been identified as an agent that can reduce enteric CH4 production from livestock significantly. However, sustainable supply of this seaweed is a problem and there are some concerns over its sustainable production and potential negative environmental impacts on the ozone layer and the health impacts of bromoform. This review collates information on seaweeds and seaweed bioactives and the documented impact on CH4 emissions in vitro and in vivo as well as associated environmental, economic and health impacts.

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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.251
GPT teacher head0.329
Teacher spread0.078 · 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

Citations179
Published2020
Admission routes1
Has abstractyes

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