Somatic cell count assessment at the quarter or cow milking level
Notice bibliographique
Résumé
The aim was to investigate whether on-line somatic cell count (SCC) assessment, when combined with electrical conductivity (EC), should be implemented at the udder quarter or at the cow level. Data were collected from 3 farms with automatic milking systems, resulting in 3,191 quarter milkings used in the analyses. Visual observations of foremilk and quarter milk samples for laboratory SCC analysis were used to define 2 gold standards. One was based on visual observation only and the other was based on a combination of visual observation and SCC (using a reference value of 500,000 cells/mL), which means that a quarter milking must have visually abnormal milk as well as an increased SCC to be categorized positive. On-line SCC assessment took place at the quarter level during the first part of the milking. Composite cow level samples were used for laboratory SCC analysis and to compare the performance of SCC assessment at quarter and cow levels. The EC at the quarter level was measured by in-line sensors of the automatic milking system. Alerts for SCC indicators were calculated based on straightforward reference values. Alerts for EC were based on straightforward reference values, or on interquarter ratios. The latter was calculated by dividing the value of a given quarter by the average value of the 2 lowest quarters of that milking. The EC and SCC indicators were combined with either a Boolean "and" or "or" function. Receiver operating characteristic curves were used to visually present results using different threshold values. Sensitivity, specificity, and success rate at the quarter level and false alert rate per 1,000 cow milkings were used to compare indicators at given sensitivity or specificity levels. Quarter level SCC assessment was superior to cow level assessment (transformed partial area under the curve=0.70 vs. 0.62) when combined with EC measurement at quarter level. When aiming for the same sensitivity level (e.g., 50%) with all visual abnormal milk as the gold standard, more false alerts were generated with cow level assessment (137 per 1,000 cow milkings) compared with quarter level SCC assessment (75 per 1,000 cow milkings). As a comparison, using EC alone resulted in 292 false alerts per 1,000 cow milkings in the same situation. Therefore, it is concluded that quarter level SCC assessment was superior to cow level assessment when combined with EC measurement at quarter level.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».