Bibliographic record
Abstract
This book presents in a skilful way the formation, development and achievements of the Surveying Engineering / Geodesy and Geomatics Engineering Department at the University of New Brunswick (UNB) from its inception to the mature age of fifty.Beginning as part of the Civil Engineering Department, it achieved in 1965 independent status as a Surveying Engineering Department, and on July 1, 1994 changed to the Geodesy and Geomatics Engineering (GGE) Department.It was the first Surveying Engineering Department in North America at university level, which provided a comprehensive, integrated education in the broad field of Surveying Science and Engineering that included geodesy, traditional surveying, photogrammetry, remote sensing, engineering and mining surveying, land information and hydrography, all that is now President of UNB), Coleman and their successors are described.The hosting of national and international conferences, and research projects in areas such as geodesy, GPS, land information, digital mapping, remote sensing and ocean mapping, reflect the interdisciplinary spectrum of the activities of the GGE Department.The establishment of the Chair of Ocean Mapping has put the Department of Geodesy and Geomatics Engineering at the international forefront in this field.The staff of GGE Department participated in international geomatics projects sponsored by CIDA in places such as the former Soviet Union
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.406 | 0.330 |
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".