Mer Bleue, Ontario, Arctic surrogate study site project 2015 - GPS survey report
Bibliographic record
Abstract
Natural Resources Canada (NRCAN) has the mandate of providing essential geographic information. An improved knowledge of our physical environment represents one of the basis of this mandate. The Arctic is an important, but difficult, area to study especially for wetland monitoring. To reduce survey costs, researchers use surrogate sites located closer to home base office; this is why the Mer Bleue Bog, featuring open space / low tree coverage, typical of Arctic environment, is used as arctic surrogate study site. This study site is used for the calibration - validation of various types of remote sensing data acquired by several project partners, and using satellite, airborne and Unmanned Aerial Vehicule (UAV) platforms. Precisely geolocated products require ground control points (reference points) which are visible to the camera of the platform and whose geographic location is known with precision. To fulfill this need, high precision GPS surveys are required. This document, highly illustrated, describes in detail the method and results of the GPS survey required for the geographic rectification of the numerous types of imagery, including Unmanned Aerial Vehicule photographs, acquired within the scope of this project in Mer Bleue bog in 2015.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.017 | 0.006 |
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".