Social Semantic Approach to Support Communication in AEC
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
Communication systems in the architecture, engineering, and construction (AEC) industry face many challenges. This paper proposes construction information and knowledge portal (CIKP), an information and knowledge-management system that utilizes three technologies to address the challenges in information exchange and knowledge sharing. First, a semantic web that is unlike typical data-exchange standards because ontologies present human knowledge in a machine-interpretable manner. This provides for more linguistic-friendly representation of tacit/subjective knowledge, which increases the level of human-friendliness of communication systems. Second, a social web, which links people (instead of documents) to create communities of practice (CoPs) and allows people to share, reconfigure, and generate knowledge. Finally, publish/subscribe (pub/sub) systems, which provide for a push-pull scenario for information exchange. In the proposed system, any knowledge item (KI) (e.g., a document, website, and blog) will be represented (tagged) with a semantic vector that describes its contents. The developer of the KI can push (share) this to his or her social network. On the other end of the spectrum, system users can build semantic profiles for their areas of expertise and/or interests. The system can pull (find) the most relevant KIs and forward them to the user. The system can also link peers with similar or complementary interest to one another to establish virtual ad hoc teams. The system was evaluated through input from two focus groups.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it