Using the Internet to Transfer Knowledge on Concrete Durability: Improving and Fostering Knowledge Exchange, eWork and eBusiness in Architecture, Engineering and Construction
Bibliographic record
Abstract
Today, in the Digital Age, the Internet is becoming the most effective medium to transfer knowledge, developed under government R&D programs, to the industry. Presenting research results on the Web allows scientists to use effective knowledge dissemination and research collaboration tools, and companies to have timely anywhere, anytime and on-demand access to valuable research information. This is especially important for AEC companies, typically small and medium size businesses, that don't have enough resources to conduct their own research or to search for information published in scientific journals and conference proceedings. Currently, in Canada, on average 9 out of 10 AEC companies are connected to the Internet. Web resources are increasingly becoming important sources of vital information for AEC companies and the proposed new knowledge dissemination model could provide excellent knowledge transfer channels for new strategic economic development directions.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.014 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".