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Potential Domoic Acid (Neurotoxin) Producing Phytoplankton Pseudonitzschia in Indian Coastal Water - do We Need to Care?

2023· article· en· W4382700064 on OpenAlexaboutno aff
Gunjan Motwani, R. Soundar Rajan, Mini Raman, Hitesh Solanki -

Bibliographic record

VenueInternational Journal For Multidisciplinary Research · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Toxins and Detection Methods
Canadian institutionsnot available
FundersScience and Engineering Research BoardSpace Applications CentreIndian Space Research Organisation
KeywordsDomoic acidPhytoplanktonNeurotoxinEcologyFisheryEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Pseudonitzschia species are potential domoic acid producers, a neurotoxin, responsible for the infamous human HAB intoxication at Prince Edward Island, Canada in 1987, costing human lives. Global warming has widened the reach of these phytoplankton species and it is being reported in Indian waters. We report the occurrence of ten Pseudonitzschia species in the northwestern coastal waters of India, out of which, seven are potential domoic acid producers. The question arises, are we vulnerable to HAB (Domoic Acid) toxicity? In light of the observation that Pseudonitzschia dominates the coastal waters of Veraval and its abundance is increasing with time, the present study briefly synthesizes the available information on the ecology, metabolism, and other relevant knowledge related to the domoic acid production by Pseudonitzschia and assesses the risk of human intoxication through trend and forecast analysis with the possible preventive measures required.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.046
GPT teacher head0.407
Teacher spread0.361 · 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
GenreEmpirical

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

Citations1
Published2023
Admission routes1
Has abstractyes

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