A multiagency and multijurisdictional approach to mapping the glacial deposits of the Great Lakes region in three dimensions
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 Great Lakes Geologic Mapping Coalition (GLGMC), consisting of state geological surveys from all eight Great Lakes states, the Ontario Geological Survey, and the U.S. Geological Survey, was conceived out of a societal need for unbiased and scientifically defensible geologic information on the shallow subsurface, particularly the delineation, interpretation, and viability of groundwater resources. Only a small percentage (<10%) of the region had been mapped in the subsurface, and there was recognition that no single agency had the financial, intellectual, or physical resources to conduct such a massive geologic mapping effort at a detailed scale over a wide jurisdiction. The GLGMC provides a strategy for generating financial and stakeholder support for three-dimensional (3-D) geologic mapping, pooling of physical and personnel resources, and sharing of mapping and technological expertise to characterize the thick cover of glacial sediments. Since its inception in 1997, the GLGMC partners have conducted detailed surficial and 3-D geologic mapping within all jurisdictions, and concurrent significant scientific advancements have been made to increase understanding of the history and framework of geologic processes. More importantly, scientific information has been provided to public policymakers in understandable formats, emphasis has been placed on training early-career scientists in new mapping techniques and emerging technologies, and a successful model has been developed of state/provincial and federal collaboration focused on geologic mapping, as evidenced by this program's unprecedented and long-term successful experiment of 10 geological surveys working together to address common issues.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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