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Record W2030024982 · doi:10.1081/txr-100100317

TOXINS ASSOCIATED WITH MEDICINAL AND EDIBLE SEAWEEDS

2000· article· en· W2030024982 on OpenAlexaboutno aff
Tatsuo Higa, Masayuki Kuniyoshi

Bibliographic record

VenueJournal of Toxicology Toxin Reviews · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Toxins and Detection Methods
Canadian institutionsnot available
Fundersnot available
KeywordsDomoic acidBiologyUlvophyceaeBotanyGenusAlgaeZoologyToxinChlorophytaMicrobiology

Abstract

fetched live from OpenAlex

Toxins associated with medicinal and edible seaweeds are reviewed with an emphasis on chemistry. The red alga Digenea simplex has been used for the treatment of roundworm disease for centuries. Its active principle is kainic acid . The related domoic acid is a constituent of another red alga, Chondria armata, used for the same purpose. These compounds known as kainoids are potent neurotoxins and excitatory amino acids. Kainoids are important tools in neurophysiological research. Domoic acids are also produced by diatoms and were responsible for the shellfish poisonings known as amnesic shellfish poisonings which occurred in Canada in 1987. Caulerpin and Caulerpicin have been described as toxic constituents of edible species of the green algal genus Caulerpa, but evidences in later studies indicate that they have no acute toxicity. Caulerpin, which has a structure related to auxin, promotes plant growth. Caulerpenyne, a toxic constituent of Caulerpa taxifolia and other inedible species, has been evaluated for its ecotoxicological effect in the Mediterranean where C. taxifolia bloomed explosively. Three different classes of compounds have been identified in the poisonings with species in the genus Gracilaria. They are prostaglandin E2 from G. verrucosa in Japan, aplysiatoxins and related compounds from G. coronopifolia in Hawaii, and polycavernosides from G. tsudai in Guam.

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: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.022
GPT teacher head0.289
Teacher spread0.267 · 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 designObservational
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

Citations51
Published2000
Admission routes1
Has abstractyes

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