Geovisualization of Mercury Contamination in Lake St. Clair Sediments
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 Laurentian Great Lakes of North America contain approximately 20% of the earth’s fresh water. Smaller lakes, rivers and channels connect the lakes to the St. Lawrence Seaway, creating an interconnected freshwater and marine ecosystem. The largest delta system in the Great Lakes is located in the northeastern portion of Lake St. Clair. This article focuses on the geovisualization of total mercury pollution from sediment samples that were collected in 1970, 1974 and 2001. To assess contamination patterns, dot maps were created and compared with surfaces that were generated using the kriging spatial interpolation technique. Bathymetry data were utilized in geovisualization procedures to develop three-dimensional representations of the contaminant surfaces. Lake St. Clair generally has higher levels of contamination in deeper parts of the lake, in the dredged shipping route through the lake and in proximity to the main outflow channels through the St. Clair delta. Mercury pollution levels were well above the Probable Effect Level in large portions of the lake in both 1970 and 1974. Lower contaminant concentrations were observed in the 2001 data. Lake-wide spatial distributions are discernable using the kriging technique; however, they are much more apparent when they are geovisualized using bathymetry data.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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