An evolutionary model of glacial dispersal and till genesis in Maritime Canada
Bibliographic record
Abstract
Abstract Glacier process models of till genesis cannot fully explain the properties of tills in Maritime Canada. A succession of local ice caps, called the Appalachian Ice Complex, developed during the last glaciation and were drained by ice streams into the submarine channels bordering the region. The migration of these centres produced areas with widely differing flow patterns, landform assemblages and deposits. Early regional phases of ice flow were characterized by wide, rapidly-flowing ice-streams that formed thick exotic, silty tills. In later phases, ice divides developed over highland areas underlain by metamorphic and igneous rocks, forming stony local tills. Terrain zones characterized by distinct transport histories and depositional sequences were produced by the interplay and migration of regional ice sheets and local ice caps. The interaction of local glaciers and previously deposited tills formed hybrid tills through two reworking processes: inheritance and overprinting. Inheritance is incorporation of till components and/or fabric into a younger till by erosion and entrainment of material from an older till. Overprinting is the injection or imprint of matrix, clasts or fabric on older tills by overriding ice. Glacial dispersal of rocks, minerals and trace elements in this complex glaciated terrain is controlled by the location of former ice divides. Simple unidirectional trains are preserved in relict terrains under divides. In ice marginal areas, reworking processes result in complex dispersal fans produced by smearing and widening of previously formed trains and fans. These dispersal fans can be modelled by vector addition of discrete flow events within each dispersal zone. A simple empirical model of glacier dispersal is presented using exponential decay and uptake algorithms, and incorporating the reworking of older till material.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".