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Record W3138187464

Determination Of Some Heavy Metals In Selected Cosmetic Products Sold At Iraqi Markets

2020· article· en· W3138187464 on OpenAlexaboutno aff
Riyadh Mohammed Jihad

Bibliographic record

VenueSystematic Reviews in Pharmacy · 2020
Typearticle
Languageen
FieldChemistry
TopicHeavy Metals in Plants
Canadian institutionsnot available
Fundersnot available
KeywordsCadmiumLipstickArsenicCosmeticsHeavy metalsAtomic absorption spectroscopyEnvironmental chemistryEnvironmental scienceToxicologyChemistryPhysics
DOInot available

Abstract

fetched live from OpenAlex

The content of arsenic, lead and cadmium in different items of cosmetics was estimated using flame atomic absorption spectrometry. Twenty samples with four brands (lipstick, foundation, eyeliner and eyeshadow) were chosen from cosmetic stores in Anbar, Iraq. After they have been analyzed, The results revealed that the level of lead in the lipstick, foundation, eyeliner and eyeshadow was within the range of 3.16 - 9.47 , 1.05 – 9.47 , 3.16 – 8.00 and 6.84 – 9.68 μg.g-1 , respectively. The content of lead and cadmium in items used is lower than the permissible limits according to a health Canada establishment. While the arsenic concentration in all items used in this study is higher than the permissible limits according to a health Canada establishment.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.093
GPT teacher head0.347
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

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

Citations6
Published2020
Admission routes1
Has abstractyes

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Same venueSystematic Reviews in PharmacySame topicHeavy Metals in PlantsFrench-language works237,207