GPR stratigraphy used to infer transgressive deposition of spits and a barrier, Lake Bonneville, Stockton, Utah, USA
Bibliographic record
Abstract
Abstract Ground penetrating radar (GPR) stratigraphic profiles of the classic cross-valley barrier and associated spits of Late Pleistocene Lake Bonneville, near Stockton, Utah, are used to infer transgressive depositional style and internal sedimentary structures. From onlapping patterns of radar reflections, which mimic subsurface stratigraphy, we reconstruct the following depositional sequence and style: (1) at the north end of the Rush Valley, the barrier formed by vertical accretion while keeping pace with hydro-isostatic-forced basin subsidence and/or slow lake-level rise; (2) a reorientation of the longshore transport pathway, induced by continued basin subsidence and/or a lake-level rise, produced a spit that prograded 2.5 km southwestward into Rush Valley. The NW-dipping radar reflections from the spit onlap SE-dipping reflections from the back-barrier, indicating that this spit was deposited after the barrier; (3) a final rise in lake level and/or basin subsidence again reoriented longshore transport and deposited the smaller upper spit. Radar reflections from the upper spit onlap the proximal eastern margin of the Stockton spit. This upper spit is the final landform deposited during the Bonneville highstand. The depositional sequence inferred from radar stratigraphy agrees with the transgressive hypothesis formulated in 1890 by G. K. Gilbert.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".