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Enregistrement W4391777677 · doi:10.1051/bioconf/20236803028

Tracing and tracking wine bottles: Protecting consumers and producers

2023· article· en· W4391777677 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

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Notice bibliographique

RevueBIO Web of Conferences · 2023
Typearticle
Langueen
DomaineBusiness, Management and Accounting
ThématiqueWine Industry and Tourism
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésTracingWineBusinessTracking (education)CommerceComputer securityAdvertisingComputer scienceFood scienceChemistrySociology

Résumé

récupéré en direct d'OpenAlex

The effective tracking and tracing of wine bottles is critical to ensure consumers are receiving high quality wine from the place of origin that is stated on the label and produced from grapes grown in that place. Wine production and its supply chain are controlled by different laws around the globe. From the International Organization of Vine and Wine (OIV) to the European Union (EU) and other national governments, suppliers and producers are required to provide specific documentation as the wines make their way to consumers. However, the wine industry loses billions from counterfeit wine and illicit trade. That is why the improvement of the methods applied to verify the origin and the quality of wines is important to protect wine consumers and producers. This short presentation explores what members of the Wine Origins Alliance (WOA) are doing within their respected regions to effectively trace and track their wine bottles along the entire value chain, with intelligent labeling and data recording through effective technology. Specifically, WOA provides case studies from its members that give an overview of the methods they have implemented (or are working to implement) to ensure consumers know the true origins of the wine. Their commitment to quality, traceability, and transparency are the very reasons why these regions are considered among the most renowned across the globe. Below are a few examples of the case studies that will be presented. * Chianti Classico. All the wines can be traced from the vineyard to the bottle as the entire production is monitored and recorded. Each bottle must be adorned with a government-issued label on the bottle neck, which contains an alphanumeric code that consumers can use to access the wine’s official chemical analysis and quantity bottled on the open database located on the Chianti Classico website. * Champagne. The General Syndicate of Winegrowers in Champagne (SGV) contracted with Advanced Track & Trace to supply the CLOE caps, which feature a unique serialized code and hologram. A QR code customized to the Champagne grower’s visual identity, which appears on the exterior of the cap, offers customers “access to each bottle's unique information, concealed on the inside of the cap. That includes a serial number, signature, message and illustration of the brand, as well as the ability to check the bottle's origin.” * Rioja. All wine bottles produced in the region are required to include numbered seals for specific zones or municipalities. But, in the Rioja Alta zone, producers have been using artificial vision to photograph each bottle, scanning the code and marking it on the bottle with ultraviolet (UV) link and integrating it into each winery’s computer systems, allowing wineries “to identify and monitor each and every bottle individually, from the moment the wine is labelled until it is delivered to every client, distributor or importer anywhere in the world.”

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,117
Score d'incertitude au seuil0,391

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,045
Tête enseignante GPT0,250
Écart entre enseignants0,205 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle