Determination of Bedrock Weathering Rates in the Juneau Area, Northern Southeast Alaska - Abstract
Bibliographic record
Abstract
Stainless steel bolts (7.94 x 38.10 mm) were drilled and epoxied into bedrock study areas in the Gravina, Taku, and Great Tonalite Sill/Yukon Tanana terranes in the Auke Bay and Mendenhall Valley areas of Juneau, Alaska in the spring of 2006. These lithologies vary from zeolite facies andesite flows and graywackes, greenschist facies metabasalts and turbidites, to amphibolite facies sheared tonalite, quartzite and marble. Baseline data consisting of bolthead-to-rock surface distances were collected and georeferenced with GPS to create an initial dataset from which to compare future measurements. A specially designed micrometer Rock Erosion Meter (REM) (Allred, 2004) was utilized to measure the lowering of rock surfaces adjacent to the bolts. This measuring tool was built from a Brown and Sharp 608 model micrometer by Allred. The carbide-tipped measuring rod is able to able to measure depths between 25.4-76.2 mm from the rock bolt head. Comparative studies in southern southeast on karst surfaces in the Alexander terrane carbonates have yielded dissolution rates ranging from 31 mm/ka in forested terrains to 38 mm/ka in alpine settings. Runoff from acid peat bogs produced dissolution rates of 1.66 m/ka, which are amongst the highest rates in the world. We anticipate much lower rates for the weathering of newly deglaciated, mostly siliclastic rocks in the Juneau Area.
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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 | 0.001 | 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".