Integrating an expert system with BrIMS, cost estimation, and linear scheduling at conceptual design stage of bridge projects
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Highway networks are a major infrastructure system, most crucially major bridges and motorways. Proper handling of highway networks plays a significant role in enhancing the functionality of a bridge network. Besides that, estimating bridge construction costs is an increasing necessity at the conceptual design stage for accurate budgeting and effective funding. The degree of subjectivity involved in decision making of bridge projects is the main factor that influences bridge cost estimation and linear scheduling at the conceptual design stage. Objectives of this study are intended to demonstrate the viability of integrating a decision support system comprising qualitative objective functions with a bridge information management system (BrIMS) in order to overcome subjectivity in decision makings. An external data interchange protocol is implemented in synchrony with interoperability standards. The deployment of the proposed system shall include an all-in-one bridge construction cost estimation tool that can provide users with recommendations for bridge design alternatives. An integration of an expert system, cost estimation, and linear scheduling is proposed by automating cost and time scheduling techniques at the conceptual design stage. Successful implementation of such a system is a technological achievement of novelty to the integration of BrIMS solutions with probabilistic fuzzy logic strategic approaches.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 it