International Journal of 3-D Information Modeling
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
Subsurface construction operations require accurate and reliable information about underground conditions.Utility owners in nearly all developed cities face the challenge of obtaining and integrating such information in their professional planning, construction and maintenance processes.Meanwhile, smart city initiatives proliferate, and potentially make cities' underground infrastructures even more dense, complex and entangled.Such developments are pushing society to create underground data models, to populate these models, and to mobilize them in subsurface engineering and urban planning practices.This not only makes streetworks more efficient, but also helps to avoid damage to existing infrastructures, and to avoid harm to construction workers and the public.To manage the underground better, we argue that a diverse set of 'underground research communities' should be brought together.Specifically, there exists a need to (a) establish methodologies to extract information about underground conditions from the field; (b) develop models that capture underground ontologies, and contribute to standardization and interoperability between next-generation IT-systems; and, (c) advance the use of such systems to support planning, design, engineering and maintenance of the underground infrastructure life cycle.This special issue is a first attempt to develop these varying perspectives together into an underground infrastructure research community.This IJ3DIM special issue includes contributions from a range of disciplines covering informatics, geophysics, construction management, and urban planning.The three distinct perspectives included in the issue studied the underground realm, each focusing on various stakeholder and stages of the lifecycle of an underground network.Contributions elaborate processes from analysis and onsite data collection; through modelling and representation of subsurface utility information; and communication in construction project stakeholder dialogues.It also covers multiple lifecycle stages of assets by looking at the planning, design, construction and maintenance of a utility.The issue's first contribution addresses remote sensing, and geographic information systems as tools and methods for utility surveying.The next contribution addresses how data models should subsequently register obtained network data as part of advanced visualization and simulations.The third contribution studies how end-users eventually engage with 2D and 3D models of the underground to facilitate architectural design and urban planning.Specifically, Tabarro, Pouliot, Losier, and Fortier developed an approach to using existing geographical data from the web to facilitate utility surveying.Their WebGIS approach integrates geographical utility data models on-the-fly with sensor data from ground penetrating radars (GPRs).In an exploratory implementation study, the authors investigate how the approach helps localizing, marking and geo-annotating utilities, and how it creates benefits for potential end-users in Canada and Brazil.This showcases how GPR can become a more widely used tool to map city undergrounds.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.007 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 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 it