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Record W2921260301 · doi:10.1080/19440049.2019.1581380

Analytical screening of marine algal toxins for seafood safety assessment in a protected Mediterranean shallow water environment

2019· article· en· W2921260301 on OpenAlex
Monica Mattarozzi, Antonella Cavazza, Anna Calfapietra, Monica Cangini, Silvia Pigozzi, Federica Bianchi, Maria Careri

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFood Additives & Contaminants Part A · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Toxins and Detection Methods
Canadian institutionsnot available
FundersNational Research Council Canada
KeywordsMediterranean climateWater safetyEnvironmental scienceFisheryAlgal bloomMediterranean seaOceanographyWaves and shallow waterWater qualityEcologyBiologyGeologyPhytoplankton

Abstract

fetched live from OpenAlex

Microalgal species growing in marine and aquaculture environments can be responsible for harmful events because of their ability to produce potent natural toxins that can accumulate in edible mollusc species. Their consumption can cause severe illness and even be lethal. The European Union provides comprehensive regulations covering various general food safety aspects to manage the risk of contamination in shellfish farms. Many analytical methods have been proposed to evaluate algal toxins presence in the environment and in food products, for conducting surveillance studies of the main molluscs production sites and, where necessary, immediate monitoring of possible contamination of shellfish. In this work, a one-year analytical surveillance study was carried out to verify the possible presence of algal biotoxins in molluscs from a Mediterranean breeding area. Water and molluscs were sampled from a district of the North-East coast of Sicily, consisting of a unique brackish ecosystem of two lakes connected to each other and to the sea by narrow canals. Water samples were collected to investigate phytoplankton i by microscope analysis to assess the presence of potentially toxin-producing species, such as Pseudo-nitzschia spp, Alexandrium spp and Gonyaulax spinifera, although the presence of toxic phytoplankton has never reached alert levels. Mussels and clams samples were submitted to analysis of paralytic shellfish poisoning toxins, amnesic shellfish poisoning toxins and lipophilic toxins by liquid chromatography-based methods Only a few yessotoxins were detected, having concentrations always below the regulation limits. An existing liquid chromatography-tandem mass spectrometry-based multiresidue method for lipophilic biotoxins was adopted and extended to cover emerging biotoxins such as cyclic imines. The performance of the analytical method for Gymnodimine A and Spirolide 13-desMeC was assessed, obtaining respective quantitation limits of 20 and 10 µg kg−1, a precision always lower than 13% and trueness in the 81–120% range. Method applicability was confirmed using certified materials and a naturally contaminated sample.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.423
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0230.000

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 head0.024
GPT teacher head0.279
Teacher spread0.255 · 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