Genesis of dispersal plumes in till
Bibliographic record
Abstract
In regions formerly covered by continental ice, till sheets may contain distinctive clastic particles derived from local bedrock sources such as ore bodies. Such particles, especially in thicker tills, may be distributed in three-dimensional dispersal trains or plumes. Developments in our understanding of glacial erosion, entrainment, and deposition over the past two or three decades help clarify formation of these plumes. Much of the debris in the basal ice of ice sheets is likely incorporated at places where water is freezing onto the base of the ice sheet. This water, largely a product of melting of basal ice further upglacier, has migrated downglacier under the influence of a gradient in the hydraulic potential controlled primarily by the ice surface slope and secondarily by basal topography and thermal regime. Refreezing occurs over a substantial distance along flow, so as the ice moves away from an ore body, material eroded from the body is later elevated above the bed by refreezing of more meltwater, incorporating additional material derived from the country rock. Broadening and mixing of the plume, both vertically and horizontally, can occur by shear in the ice, by shifting ice flow directions, by collisions between particles, and by folding of basal ice layers. Further downflow, where net basal melting resumes, the debris is deposited by meltout or lodgement. Many idiosyncrasies of dispersal plumes are likely caused by non-steady-state changes in basal thermal regime.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".