Evaluation of the advisory services provided by the Food Animal Residue Avoidance Databank
Notice bibliographique
Résumé
A s part of its mission to help ensure that foods of animal origin are free of violative chemical residues, the Food Animal Residue Avoidance Databank (FARAD) offers 2 advisory services to veterinary practitioners.The first is a comprehensive online database (VetGRAM) of drugs approved by the US FDA/Center for Veterinary Medicine (CVM) for the treatment of food-producing animals.Second, FARAD offers expert-mediated advice on residue avoidance and mitigation for chemical contamination incidents and the extralabel use of drugs.This service is provided by FARAD pharmacologists and toxicologists, who can be reached by e-mail a as well as a toll-free telephone number.b VetGRAMVetGRAM is a relational database that contains regulatory information about the indications, directions for use, and withdrawal periods of drugs used in food-producing animals for therapeutic as well as production-enhancement purposes.The database is maintained and regularly updated by members of FARAD at the University of Florida at Gainesville.The first online version of VetGRAM was launched in the summer of 1999.An interface was developed that made the database searchable by species.It was made available through the Internet via the FARAD Web site, c and users could also request digital copies.Users were required to register, after which they received a user name and password that gave them access to VetGRAM.The interface has recently been updated, and a new version of VetGRAM was launched in the spring of 2003.This new version is more versatile, and the database can now be searched by any combination of species, active ingredient, trade name, drug classification, manufacturer, or new animal drug application (NADA) number.An e-mail-based survey was conducted approximately 20 months after the launch of the first version of VetGRAM.During this period, there was a mean of 50 daily hits to the FARAD Web site.Three hundred and seventy-six e-mail addresses were randomly chosen from the 1,150 subscribers to VetGRAM and compiled for the initial mailing.Of the 376 initial e-mail addresses, only 279 were found to be viable addresses.There were 143 respondents who replied to the survey (51% response rate) with 122 respondents who replied to 1 or more questions (44% adjusted response rate).The majority of respondents (86/122 [70%]) accessed VetGRAM from the United States; 12 (10%) respondents were from Canada, and 2 or more respondents were from Argentina, Australia, Mexico, Taiwan, and Turkey.Private practitioners represented the largest group of respondents (54/143 [38%]), but there were also a FARAD
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 | 0,005 | 0,003 |
| 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 | 0,001 | 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 ».