Bibliographic record
Abstract
The Finnish Road Administration (Finnra) is introducing extensive and long-term maintenance contracts. Due to long contract period, it is important to be able to make changes to the contract, as well as changes to the level of services and changes in inventory. The costs of these changes are relatively small compared with the total costs of the maintenance contracts. The main point of this survey is to examine problems when changes are made to the maintenance contracts and consider the possible solutions. To examine problems of today the Finnras maintenance management group and contacts were interviewed. There is not actual agreed method to procure modification and extra work. According to survey, the two biggest problems were the lack of competitive prices and regional differences of procurement of extra work. The procurement methods in Canada, England and other Northern countries were analysed as a part of this study contain interesting details. level of services which are specified in the contract. The winter maintenance is ca. 60% of the costs of the maintenance contracts and thus the costs of changes in the level of service in winter maintenance could grow relatively high. Summer maintenance includes more duties and the costs are lower than winter maintenance. Definition of the costs of a change should be easier. A more comprehensive price list must be attached to the call of bids. For example winter maintenance must be priced by activities and level of service. In case of a change these prices are used to determine the increase or decrease of the costs. The procurement of extra work can be made more effective. The primary way is to create larger packet of extra works and include them in the call of bids. The packets, which are created during the contract period, must be competed separately outside the maintenance contract. The single works should be done through competed unit prices used in the maintenance contract. Besides the actual maintenance work the contracts consist of administrative work such as reporting. As a rule the changes in administrator works should be done without any costs. Only the compensations of major changes should be negotiated between the contractor and the purchaser. This report may be found at http://alk.tiehallinto.fi/julkaisut/pdf/3200966-v-muutostenhall_alueurakan_hankintamenettelyssa.pdf
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".