CCQM-K158 elements and inorganic arsenic in rice flour
Notice bibliographique
Résumé
Main text KRISS and NMIJ jointly coordinated the CCQM-K158 comparison on elements and inorganic As in polished rice flour. The study comprised two parts, Part A and Part B. Successful participation in formal international comparisons is essential for documenting calibration and measurement capability claims (CMCs) by national metrology institutes (NMIs) and designated institutes (DIs). CCQM-K158 specifically supports CMCs within the food category, corresponding to the sample matrix labeled "High organic content" in the new CC table for broad claims. Simultaneously, the CCQM-P200 comparison ran in parallel with the key comparison CCQM-K158. In Part A, sixteen NMIs/DIs participated. Participants were requested to measure the mass fractions of Cu, Hg, K, Na, Pb, and Sb in rice flour, expressed in mg·kg-1, on a dry mass basis. Most NMIs/DIs adopted microwave-assisted acid digestion in a closed vessel for sample pretreatment, except for NIS, which used open vessel acid digestion with heating. Majority of the participants used isotope dilution (ID) ICP-MS, except for K and Na. ICP-MS or ICP-OES with standard addition calibration and k0 INAA were also applied specially for elements of which ID is impossible or difficult to access. ICP-MS, ICP-OES, AAS methods were also used with external calibration. In Part B, fifteen NMIs/DIs participated. Participants were requested to evaluate the mass fractions, expressed in mg·kg-1, of total arsenic and inorganic arsenic (the sum of As (III) and As (V)) in polished rice flour. For total As, thirteen NMIs/DIs reported their analytical results, where all the NMIs/DIs, except for JSI, adopted ICP-MS with a microwave acid digestion. JSI adopted k0-INAA after pelletizing the sample. For inorganic As, seven NMIs/DIs reported their analytical results, where all the NMIs/DIs adopted liquid chromatography-ICP-MS with a thermostatically controlled extraction using diluted acids. The results of all the participating NMIs/DIs were evaluated against the key comparison reference value (KCRV). The KCRV and associated uncertainty were estimated from reported results, excluding outliers, using NIST decision tree (NDT) as an estimator of the KCRVs. Successful participation in CCQM-K158 Part A demonstrates measurement capabilities for determining mass fractions of alkali and alkaline earth (K, Na), transition (Cu, Hg, Pb), and metalloid/semi-metal (Sb) elements in mass fraction range above 0.05 mg kg-1, in high organic content matrices such as grains, beans, and related samples. Similarly, successful participation in CCQM-K158 Part B demonstrates measurement capabilities to determine mass fractions of total arsenic and water-soluble arsenic species such as inorganic arsenic (the sum of As (III) and As (V)), mono-, di-, tri-, and tetra-methyl arsenic compounds (MAA, DMAA, TMAO, TeMA), arsenocholine (AsC), and arsenobetaine (AsB), in mass fraction range above 0.05 mg·kg-1 in grains, beans, and related samples. To reach the main text of this paper, click on Final Report . Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/ . The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).
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 | 0,001 |
| 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 ».