Validation of an automated method to count steps while cows stand on a weighing platform and its application as a measure to detect lameness
Notice bibliographique
Résumé
Weight shifting between legs and steps taken when cows stand may be a useful tool to assess cow comfort and lameness. Weight shifting is assessed by measuring the distribution of weight applied to each leg when standing on a weighing platform, whereas frequency of steps is traditionally measured with live observation or video recording. The objectives of this study were to validate an automated method to count steps from weight distribution measurements (experiment 1) and to assess the accuracy of the frequency of steps in detecting lameness (experiment 2). In experiment 1, 6 nonlame multiparous cows stood on a weighing platform covered with either concrete or rubber (1h/cow per surface) while stepping behavior was video recorded. Receiver operating characteristic curves were constructed, using the steps observed in the video recordings as the gold standard, to calculate the optimal threshold (based on the sum of sensitivity and specificity) of the weight applied to a leg to define a step. Optimal thresholds were similar between surfaces. The optimal thresholds, when pooling the 2 surfaces, were 127 and 98 kg for the front and rear pair for legs, respectively, with a specificity and sensitivity ≥0.96. Thresholds were used to construct an algorithm to count steps. In experiment 2, 57 cows (26 of them considered lame according to their gait score) stood for 15 min on the weighing platform. Frequency of steps taken with the front and rear pair of legs was calculated from the weight distribution measurements using the algorithm calculated in experiment 1. Lame cows took more steps per minute with the rear legs than did nonlame cows (1.6 vs. 1.0 steps/min; SE of the difference=0.2). As previously shown for weight shifting, the frequency of steps taken with the rear legs was a good predictor of lameness (area under the curve of the receiver operating characteristic curve=0.67; 95% confidence interval=0.52, 0.81). A positive relationship was observed between the frequency of steps and weight shifting (measured as SD of the weight applied over time to the legs) in both the front (R(2)=0.35) and rear (R(2)=0.49) legs, yet the slopes differed from 1 and the intercepts differed from 0, indicating that the 2 measures were related but not the same. In conclusion, weighing platforms can accurately calculate the frequency of steps automatically, and this measure shows promise as a tool to assess lameness.
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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 | 0,002 | 0,000 |
| 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 | 0,001 |
| 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 ».