Unconsolidated sediment thickness mapping by waterborne geophysics along the Lake Michigan shoreline
Bibliographic record
Abstract
Mapping unconsolidated sediment at the Illinois Lake Michigan shoreline (ILMS) is complex but vital for sustainable management and use of this dynamic system which undergoes significant redistribution of sand in the littoral transport system over time. To understand erosion and accretion processes it is critical to map the ILMS sediments at high spatiotemporal resolution. Here we used two geophysical methods, waterborne electrical resistivity imaging (wERI) and sub-bottom profiling (SBP), ground-truthed by hydraulic jet probing and historic borings, to map the thickness of unconsolidated sediments along two reaches of the ILMS. These geophysical surveys show that the sediments have not undergone deformation, and the thickness of the unconsolidated sandy material ranges between 4 and 5 m over semiconsolidated clay and bedrock. Both geophysical methods agree with jet probe results which provide direct evidence of loose, sandy sediments up to depths of 4 to 5 m below the lakebed. The wERI shows more detailed variation in the sediment and bedrock topography than the other methods. Overall, the geophysical methods, particularly the wERI, appear to be effective tools to map the sediment structure along the ILMS at high spatial resolution. Considering the relatively low cost of the operation of geophysical surveys, simplicity of operation and data analyses, wERI and SBP show promising potential for comprehensive mapping of the ILMS. The methods supplement the limited extent of direct sampling and the lower spatial resolution but great extent of airborne geophysics, and provide the information needed for better understanding of sediment transport mechanisms.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".