Making a three-dimensional model of Halifax Harbour, Nova Scotia, Canada
Bibliographic record
Abstract
Halifax Harbour is one of best-studied harbours in the world. Researchers at the Bedford Institute of Oceanography map the seabed, perform geochemical analyses of sediment core samples, measure currents and tides and study the effects of pollution on the biota. To illustrate the complexity and intricate detail that exists on the seabed, a physical relief model of the harbour and surrounding area was constructed using the most recent technology. The model, which was milled from lightweight surfboard foam, shows underwater relief (bathymetry) as well as the land topography. Onshore, high-resolution satellite imagery was "draped" over the topographic relief using a specially designed 3-D plotter. In underwater areas, bathymetry is represented by a suite of colours ranging from light blue, to indicate shallow areas, to darker blue for deeper water. Computer generated shading was applied to emphasize detailed texture. Four "zoom" panels were also produced to focus on some of the finer details that are evident in the seabed. These details help us understand more about the harbour's geological history as well as the processes that are active today, both natural and man-made. This poster explains the many stages in the process of creating the Halifax Harbour relief model.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".