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Record W2892605189 · doi:10.5539/apr.v10n5p74

Radiocesium Contamination in Samples of Blueberries Jams Collected in Stores of NE Italy (2013-2017)

2018· article· en· W2892605189 on OpenAlexvenueno aff
Massimo Calabrese, Antonella Calabretti, Chiara Cantaluppi, Federica Ceccotto, Daniele Zannoni

Bibliographic record

VenueApplied Physics Research · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRadiation Effects and Dosimetry
Canadian institutionsnot available
Fundersnot available
KeywordsContaminationEnvironmental scienceEuropean unionConsumer safetyJAMSEnvironmental protectionBusinessChemistryFood scienceRisk analysis (engineering)BiologyInternational tradeEcology

Abstract

fetched live from OpenAlex

The monitoring of radioactivity in foodstuffs is carried out for the purposes of food safety in order to follow the evolution of the contamination as result of incidents that occurred both in the past (eg Chernobyl) and in more recent times (eg, Fukushima). Then, the movement of goods from these countries to European Union may cause the propagation of foods potentially toxic for health. At the Port of Trieste, in the period of September 2013, some loads of blueberries (Vaccinum mirtyllus L.) were examined within the application of EC Regulation 733/2008, on the conditions governing imports of agricultural products originating in the countries affected by the nuclear accident of Chernobyl in 1986. The fruits came from Ukraine and were intended for the food preparations containing blueberries, in particular jams and marmalades. As in some cases significant values of Radiocesium concentrations (Cesium-137) were found in blueberries, though below the limit of 600 Bq/kg as required by the Regulations, it was decided to verify whether the presence of this contaminant in the raw material at the tested levels could interest the finished products. In this work, we have therefore collected and analyzed some samples of concentrated blueberries products in different large stores, in order to verify the magnitude of the possible contamination by radio Cesium.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.771
Threshold uncertainty score0.421

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.059
GPT teacher head0.317
Teacher spread0.258 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2018
Admission routes1
Has abstractyes

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