Continuing Advances in Acute Dietary Risk Assessment for Agrochemicals
Notice bibliographique
Résumé
P-637 Abstract: A range of practices currently exist within regulatory agencies worldwide for assessing the risk from human dietary consumption of agrochemicals used for plant protection. For instance, EU Authorities generally conduct dietary risk analyses using deterministic models based on single point residue values. In The United States and Canada regulators conduct probabilistic analyses of acute dietary risk using the range of available residue data and extensive information on dietary consumption patterns. The advantage of conducting probabilistic assessments is that a more complete and realistic understanding of potential risks from several sources of exposure (e.g. multiple food items and water) can be developed providing that reliable databases on consumption patterns and residue values are available. Typically acute risks are assessed from single dose studies assessed against consumption within a 24-hour period. Probabilistic methods, however, can be adapted to refine the risks for rapidly reversible compounds such as carbamates provided that appropriate information on the rate of reversibility and the timing of dietary consumption are available. The probabilistic, risk assessment model CARES® has been adapted to allow the effects of within-day exposure patterns to be assessed based on a minute by minute analysis for both food and drinking water consumption. Separate food and drinking water modules for minute by minute analyses have been developed within the model. The results from single modules can be combined to provide an aggregate assessment. The USDA Continuing Survey of Food Intakes by Individuals contains the appropriate time related data to construct a time series of within-day consumption of foods, not including drinking water. Additional within day drinking water consumption data were collected by Bayer CropScience to create a daily time series of within-day drinking water consumption. These consumption data were matched to an appropriate person in the CARES reference population based on statistical matching methods using demographic characteristics of the sampled individual to describe the consumption of food and drinking water on a minute (vs. 24 hour) basis. A comparison of acute dietary methodologies for assessing potential risks from a carbamate exhibiting rapidly reversible cholinesterase inhibition is presented. The evaluation includes: deterministic methods; probabilistic methods based on an arbitrary timeframe for acute effects (24h); and an assessment where the timeframe is based on the known properties of the compound. The last scenario represents the most appropriate acute dietary analysis using all available data including consumption, residues and duration of effect.
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 | 0,001 | 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 ».