Comparison of Paper- and Electronic-Formatted Hydroacoustic Data Charts used for Salmon Enumeration on the Yukon River near Pilot Station
Notice bibliographique
Résumé
The Yukon River Sonar Project estimates salmon passage through the river near Pilot Station, Alaska. The hydroacoustic data collected by the sonar is currently printed on paper charts in a series of grey marks called “traces.” Technicians count traces that were generated by fish, and these numbers are used to calculate daily abundance estimates. New technology allows the hydroacoustic data to be presented on electronic charts viewed on a computer. The electronic charts also present the data in a series of grey marks, and fish traces must be identified manually by technicians. However, the electronic charts present the data in greater detail, and settings that are used to optimize the visibility of fish traces are more easily adjusted. Both of these features may improve fish detection, which would result in more accurate estimates. Project leaders are planning to make a complete switchover from paper to electronic charts. The principle aim of this study was to compare the fish counts produced by the paper and electronic formats in order to expose any biases and explain why they occur. Due to variation in the slope of the river bottom, the area of river covered by the sonar is divided into several horizontal strata by distance from the transducer. Due to the properties of sound and the variation in the shape of fish traces at different ranges, it is possible that the level and direction of bias may differ among strata. A sample of 150 electronic files, out of approximately 1,700, from the 2008 season was selected for this comparison. Files were counted using Echotastic, a program written by AYK Regional Sonar Biologist, Carl Pfisterer. The electronic chart counts were higher than the paper chart counts for strata one through four, while the electronic counts were lower than the paper counts for stratum five (linear regression output: stratum one: slope=1.112, y-intercept=44.662, stratum two: slope=1.344, y-intercept=13.615, stratum three: slope=1.098, y-intercept=-7.052, stratum four: slope=1.077, y-intercept=-8.566, stratum five: slope=0.827, y-intercept=-0.688). Both the positive and negative biases are likely a result of improved fish detection on the electronic charts and a high level of subjectivity associated with counting fish using sonar. If project leaders conclude that these biases are acceptable, a transition from paper to electronic charts would be advantageous, although correcting for differences will be necessary to make past and future fish estimates comparable.
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 | 0,000 |
| 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 | 0,001 | 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 ».