Determination of Metallic Impurities by ICP-MS Technique in Eyeshadows Purchased in Poland. Part I
Notice bibliographique
Résumé
Eye shadows, which are products willingly and frequently used by women and even children, have been reported in literature to contain toxic metals. In this work, a total of 94 eye shadows samples available on the Polish market were collected. Eye shadow products have been selected in order to include several parameters important from the point of view of the typical consumer such as: product type (mat/pearl), consumer group (for adults and children), price range (very cheap, medium price, expensive and very expensive), color (twelve different colors were tested), manufacturer (eight brands were investigated) or country of production (four countries were included). The concentration of selected metals (Ag, Ba, Bi, Cd, Pb, Sr, Tl) was determined by ICP-MS technique after the sample extraction with a mixture of nitric acid and hydrogen peroxide in a microwave closed system. For Ag, Cd and Tl, some results were below the established limit of quantification for the employed technique. The presence of strontium, barium, lead and bismuth was confirmed in all studied samples. The obtained results for analyzed elements were, in general, quite comparable with the data reported by other authors. A small number of samples exceeding the permissible values (two samples were beyond the limit value for Cd of 0.5 mg/kg and one exceed the acceptable concentration for Pb of 10 mg/kg) also proves a relatively good condition of the Polish cosmetics market and suggests insubstantial risk for the potential consumers. The results gathered for some of the eye shadows intended for children turned out to be alarmingly high, in particular for elements such as Cd. The highest concentration of Cd reached almost 4 mg/kg, while of Pb amounted to 16 mg/kg. The presence of the statistically significant differences was confirmed for all included parameters with an exception of the color of the eye shadow. Considering the results acquired only for Cd and Pb with respect to the country of origin, the least contaminated cosmetics by metallic impurities seem to be the one produced in Canada, while the ones presenting the highest health risk among all studied eye shadows are make-up cosmetics originating from Poland and Italy. Multivariate analysis of a large data set using CA methods and PCA provided valuable information on dependencies between variables and objects.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».