Emerging Technologies for Construction Delivery
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
This synthesis presents information on the use of five emerging technologies for transportation construction projects: global positioning systems for layout, machine guidance, and quantity tracking; handheld computers for construction records; automated temperature tracking for concrete maturity monitoring; four-dimensional computer-aided drafting modeling for constructability analysis and improved communications; and web-based video cameras for remote project monitoring. The synthesis reports on the current state of each of the five technologies and their potential benefits for transportation agencies in the delivery of construction projects. The following characteristics are provided for each of the technologies: description, benefits, extent of use, barriers to use, instances of successful implementation and procedures, unresolved issues, and unintended consequences. It also discusses the current level of use and documents lessons learned from agencies with experience in implementing the targeted technologies. Other technologies discussed include virtual reality, building information models, and radio frequency identification. The information will form a foundation from which state and provincial highway agencies can begin the process of performing benefit-cost analysis as a first step to adopting those technologies that seem the most promising. A survey questionnaire was distributed to U.S. departments of transportation through a web-based survey application, and was also sent to select Canadian transportation agencies. Responses were received from agencies across the North American continent. In addition, a literature search was conducted of academic, governmental, industrial, and commercial resources to provide a solid theoretical and anecdotal basis for the review of each technology.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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