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Record W2296909515 · doi:10.3390/md14030058

Marine Natural Products from New Caledonia—A Review

2016· review· en· W2296909515 on OpenAlexfundno aff
Sofia-Eléna Motuhi, Mohamed Mehiri, Claude Payri, Stéphane Barre, Stéphane Bach

Bibliographic record

VenueMarine Drugs · 2016
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMarine Sponges and Natural Products
Canadian institutionsnot available
FundersMuséum National d'Histoire NaturelleInstitut National Du CancerCentre National de la Recherche ScientifiqueAgence Nationale de la RechercheCNIB
KeywordsNatural (archaeology)GeographyArchaeology

Abstract

fetched live from OpenAlex

Marine micro- and macroorganisms are well known to produce metabolites with high biotechnological potential. Nearly 40 years of systematic prospecting all around the New Caledonia archipelago and several successive research programs have uncovered new chemical leads from benthic and planktonic organisms. After species identification, biological and/or pharmaceutical analyses are performed on marine organisms to assess their bioactivities. A total of 3582 genera, 1107 families and 9372 species have been surveyed and more than 350 novel molecular structures have been identified. Along with their bioactivities that hold promise for therapeutic applications, most of these molecules are also potentially useful for cosmetics and food biotechnology. This review highlights the tremendous marine diversity in New Caledonia, and offers an outline of the vast possibilities for natural products, especially in the interest of pursuing collaborative fundamental research programs and developing local biotechnology programs.

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 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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.874
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.286
Teacher spread0.273 · 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 teacher head, not a consensus.

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

Citations41
Published2016
Admission routes1
Has abstractyes

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