Geological Survey of Canada 8.0: mapping the journey towards predictive geoscience
Bibliographic record
Abstract
Abstract The Geological Survey of Canada (GSC) has been furthering the geoscientific understanding of Canada since its inception in 1842, the equivalent of seven generations ago. The evolution of the activities of the GSC over this period has been driven by evolving geographic, economic and political contexts and needs. Likewise, new technologies and evolving scientific methods and models shaped broadly the successive generations of GSC geoscience activities. The most recent GSC generation presented a mixed portfolio of large framework mapping geoscience programmes, and more targeted, hypothesis-driven geoscience research, and the development of decision support products for a range of government, industry and other stakeholders needs. Entering its eighth generation, the GSC and related organizations are embracing digital technologies for applications such as the evaluation of mineral resource potential, the evaluation of risks and the early warning of earthquakes. In order to do so, the GSC will need to develop new methods and systems in co-operation with other geological survey organizations, and target its data acquisition and research to further advance its ability to respond to the evolving needs of society to navigate geology through space and time, from the past to the present, and from the present to the future.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.017 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".