Advancing the Canadian Geospatial Data Infrastructure: Innovations in Automation, Sustainability and Accessible Web Cartography for Mapping the Arctic’s Fragile Ecosystem
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
The Canadian Geospatial Data Infrastructure (CGDI) is the collection of geospatial data and the standards, policies, applications, and governance that facilitate its access, use, integration, and preservation for the benefit of and use by all Canadians.To foster innovation, inclusion, interoperability, and sustainability in geospatial data particularly in support of mapping and monitoring the Arctic's fragile ecosystems and to increase the adoption and implementation of standards, Natural Resources Canada's CGDI Division is developing the following products: Pan-Arctic Wetland Inventory Baseline derived from satellite imagery and ground-truth data using a machine learning and cloud computing classification methodology o Led by Natural Resources Canada, in collaboration with Arctic National Mapping Agencies, Arctic Council and organisations responsible for wetland conservation, a seamless Arctic wetland's dataset over millions
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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