Correlation of Wisconsin glacial events between the Eastern Great Lakes and the St. Lawrence Lowlands
Bibliographic record
Abstract
The interrelationship of the Wisconsin glaciogenic events among the Upper St. Lawrence Lowland and the eastern Great Lakes, particularly the Lake Ontario basin is controlled mainly by 3 factors: 1) presence or absence of a glacial dam across the St. Lawrence Lowland; 2) isostatic lowering or rise of the outlet of Lake Ontario, related mainly to glacial loading or unloading in the Upper St. Lawrence Lowland; 3) shifting in the regional direction of glacial movement through the Upper St. Lawrence Lowland, upglacier from it, and in the Lake Ontario basin. Changes in the above conditions result in detectable changes in lake levels, and in compositional changes of tills in the Lake Ontario basin. Crosschecking of the above relationships supports the relative sequence already proposed. However, the chronology of the events which are older than reliable finite 14C dates, may be reinterpreted by a comparison with oceanic stratigraphies. A possible re-interpretation of some late-glacial Late Wisconsin glacial fluctuations depends greatly upon the reliability of 14C dates on shells and correct interpretation of till-like deposits. For those glacial fluctuations in the St. Lawrence Lowlands which lack 14C dates, it is tempting to apply correlations with the 14C dated stratigraphie units of the Great Lakes Region, but we have to consider also possible regional differences in glacial dynamics.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".