Notice bibliographique
Résumé
In 1996, the provincial government of Alberta, Canada, outsourced highway maintenance for the provincial highway network. Private contractors were hired to perform maintenance activities under a 5-year, geographically based unit-price contract. The 1996 contracts specified the minimum number of trucks for each area, and the old Alberta Transportation (AT) shops were leased to the successful contractors. Starting in 1998, the government began selling AT maintenance shops, and by 2000 most properties were no longer under government control. Then, in the fall of 2000, the government began to transfer road authority for secondary highways from the municipal governments (i.e., counties) and more than doubled the length of the network under provincial jurisdiction. Prospective contractors for contracts tendered after 2001 were required to propose new shop locations and the shop size and number of trucks to be provided in their new contract area. AT's tasks were to benchmark the existing (2000) winter maintenance service on the existing network; predict the requirements for the number of trucks needed to meet provincial standards on the new (expanded) network and provide the same level of performance; and evaluate contract proposals when shop locations and number of plow trucks were not specified. The department's solution was a spreadsheet model of plowing and sanding-salting times with the total calculated time to complete one pass of the entire network as the benchmark. The model was used to determine how many trucks to add within each district as the secondary highways were transferred to provincial control. Contract proposals from prospective contractors were evaluated on whether their proposals showed equal to or slightly better than benchmark parameters. In broad terms, the benchmark model was developed by breaking the highway network into areas with similar traffic volumes, calculating the paved area (2-lane equivalent km) per plow truck, adding the newly transferred highways to the network, and determining the number of new trucks needed to complete work on the whole network within allowable times. This paper gives details of the benchmarking process, including assumptions used, how highway topography and geometric characteristics were used to affect the length of highway each plow truck can be assigned before it was fully allocated, the business rules chosen to model actual work habits, calculations used to determine the time required to plow and spread sand or salt over each segment, and the improvements made over three successive rounds of tendering.
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 | 0,000 | 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 | 0,000 |
| 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 ».