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Record W3085596003 · doi:10.1016/j.heliyon.2020.e04908

ICP-OES assisted determination of the metal content of some fruit juices from Yemen's market

2020· article· en· W3085596003 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHeliyon · 2020
Typearticle
Languageen
FieldChemistry
TopicHeavy Metals in Plants
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsInductively coupled plasma atomic emission spectroscopyCadmiumFruit juiceChemistryFood scienceOrange (colour)ContaminationZincEnvironmental chemistryInductively coupled plasmaChromiumOrange juiceFood contaminantHorticultureBiologyPhysics

Abstract

fetched live from OpenAlex

The levels of Cd, Cr, Cu, Pb, Zn, Sn, and Fe of 37 samples of 6 types of fruit juices (orange, mango, guava, pineapple, peach, and mixed fruit) marketed by different brands and of easy access in Sana'a food stores, Yemen (2019) were evaluated using the inductively coupled plasma-optical emission spectrometry (ICP-OES) technique. Traces of chromium were detected in two fruit juices and cadmium in seven juices. One sample presented a highly elevated Pb-content. High level of tin, iron and zinc were detected in some fruit juices. Metal content in some fruit juices sold on the Yemeni market exceeded the permissible limits set by health organizations for drinking water. The origin of metal contamination could be likely linked to war condition even though it is difficult to be totally affirmative, so far. Fruit juices available on the Yemeni market are globally safe, nonetheless, further risk-based surveillance studies must be carried out to decrease child exposure to toxic metals from fruit juice sources.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.000

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 head0.061
GPT teacher head0.265
Teacher spread0.204 · 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