Web-based collaborative decision support services for river runoff and flood risk prediction in the Oak Ridge Moraine Area, Canada
Bibliographic record
Abstract
River runoff is highly related to the precipitation events and the land use characteristics. It is an important component in the hydrologic cycle because of its relationship to issues such as flood and water quantity. The Oak Ridge Moraine (ORM) Area, Southern Ontario has always been faced with the impacts of extreme hydrological events. Flood not only has an impact on the ORM economical, social well-being and particularly public safety, but also exacerbates major environmental problems. Prediction of flood is a complex system of which involves variable factors including climate condition, basin attributes, land use/cover types and ground water discharge. The application of flood prediction model requires the efficient management of large spatial and temporal datasets, which involves data acquisition, storage, and processing, as well as manipulation, reporting and display results. The complexity of flood prediction makes it difficult for individual organization to deal effectively with decision-making. Difficulty in linking data, analysis tools and models across organization is one of the barriers to be overcome in developing integrated river runoff and flood risks prediction system. Therefore, it is required to develop a standardized framework for Web-based Collaborative Decision Support Services (WCDSS), supporting information exchange and knowledge and model sharing from different organizations on the web. Such a WCDSS supply both metadata services, geo-data services and geo-processing services to help collaborative decision-making, not only support distributed data sharing and services, but also support distributed model sharing and services. This paper develop a WCDSS that provides a comprehensive environment for on-line river runoff and flood risk prediction, integrating information retrieval, analysis and model analysis for information sharing and decision-making support. Such a SDSS will improve understanding of the environmental, planning and management issues and emergency management and response associated with the ORM's water environment, and to develop sustainable solutions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".