Bibliographic record
Abstract
In the field of urban infrastructure, there is a lack of models that can support knowledge management. Most efforts in the domain have focused on the creation of data models that are more suitable for the organization of static data than the creation and maintenance of dynamic domain-knowledge. In this regard, ontologies have emerged as a promising tool for interoperability and knowledge management. This research aims to establish a knowledge-enabled system to support the collaborative routing of buried urban infrastructure utilities. The routing problem is addressed at both the street level (micro) and city level (macro). The routing problem considers aspects of life cycle costing, sustainability, and community impacts. The ontologies were created by integrating and streamlining several data models currently used in the utilities sector and embedding knowledge from the design of eight major infrastructure projects in Ontario. The ontologies were implemented using the Web Ontology Language (OWL). Knowledge pertaining to micro-level routing was represented using a spatial constraint model embedded within the ontology. The model was populated with knowledge from experienced infrastructure designers. At the macro-level, knowledge was represented using a fuzzy inference system linked to the ontology. A data wrapping approach was used to bridge the gap between existing database driven systems and the knowledgebase structure of the ontology. The ontologies and decision-support systems were subsequently evaluated through (1) Validation by domain experts, (2) Creating an application ontology to model the knowledge involved in trenchless technology selection, and (3) Testing on two watermain replacement projects in the City of Toronto. The objectives of this research are; (1) Creation of a domain ontology for urban infrastructure products and related concepts, (2) Creation of an application ontology for design coordination of co-located urban infrastructure, (3) Creation of a decision-support system to support the collaborative routing of buried urban infrastructure at the micro- and macro levels, (4) Implementation of a prototype web-based GIS portai based on the ontologies and decision-support system.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".