Sedimentäre Befunde über deglaziale Schmelzwasserausbrüche aus dem Laurentischen Eisstrom
Bibliographic record
Abstract
Sediments derived from the eastern Canadian Continental Margin preserved the whole records of deglacial meltwater discharges since the Wisconsinan when the entire margin was glaciated by the Laurentide Ice Sheet. Large volume of meltwater or iceberg release were created when the ice sheet began to landward shrink and retreat. Such discharges and calving events caused erosion of the bedrocks and delivered the terrestrial sediments to the adjoining shelf and fan system. Ice streams are believed to play a major role of Ice sheet movement. The Laurentian Channel Ice Stream (LCIS) and numerous canyons on the slopes are the main pathway for the sub-glacial meltwater discharge from Gulf of St. Lawrence. Thick reddish mud event layers deposited on the Laurentian Fan have been recognized as representing deposits of the major meltwater discharges between Heinrich Event 2 and 1. Those reddish sediments were sourced from Permo-Carboniferous redbeds and created by subglacial outburst floods events. However, the event chronology and scenarios are lacking understanding, the compositions and provenance of the event beds are still unknown and the correlation to the Laurentide Ice Sheet retreat history is also unclear. In the framework of this thesis, I investigate three new sediment cores (GeoB18514-2, 18515-1 and 18516-2) retrieved from the southwestern Grand Banks slope and stratigraphically link these cores to eastern Laurentian Fan core MD95-2029, further to the Scotia Margin cores 99036-008, 99036-028 and 99036-057. In addition, 80 estuarine and coastal reference samples among the Gulf of St. Lawrence area and Newfoundland were collected to represent all major source rock lithologies. High-resolution granulometric, rock magnetic, radiographic, colorimetric core logs and radiocarbon dates as well as the geochemical properties (major elements, trace elements) were produced for the cores. Subsequently the properties of the event beds samples are compared with the reference samples from the potential source areas. Such interdisciplinary approaches allow us to better understand the red mud event beds story.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".