Case-Based Reasoning System for Modeling Infrastructure Deterioration
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
Deterioration models are essential components of infrastructure management systems (IMSs) because they predict the future condition of infrastructure facilities and consequently assist in optimizing maintenance decisions. Case-based reasoning (CBR) is proposed to generate deterioration models that benefit from the large amount of facility data stored in IMS databases and updated on a regular basis. CBRMID (CBR for modeling infrastructure deterioration) is a new CBR system developed to satisfy the special requirements of modeling infrastructure deterioration and to provide government agencies with practical, accurate, and versatile deterioration models. CBRMID is required to support (1) hierarchial decomposition of infrastructure facilities; (2) representation of facility component interactions; (3) versatility and extensibility of case and knowledge representation; (4) data reusing and sharing; (5) representation of time-dependent data; and (6) fuzziness of retrieval knowledge. In this paper, the architecture of CBRMID is described in terms of case representation, case retrieval, case adaptation, and case accumulation. An application example generated using CBRMID is also presented.
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.
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 | 0.001 | 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 | 0.000 |
| 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