Grain-size characteristics and provenance of ice-proximal glacial marine sediments
Bibliographic record
Abstract
Abstract This paper addresses the issue of the characteristic grain-size spectra of glacial and glacial marine sediments, an important topic because of the increasing emphasis on the use of specific sand-size fractions as indicators of iceberg rafting. Different methods of IRD identification can lead to different palaeoclimatic interpretations. We use three methods of grain-size analyses, with examples from the Labrador Sea, East Greenland, North Iceland, and the Ross Sea, Antarctica. The first method illustrates the ‘real’ grain size of glacial marine sediments by an examination of X-radiographs by image analysis and the sizing of clasts larger than 2 mm. Typically, grain-size analyses only apply to the matrix fraction of the sediment (smaller than 2 mm), and ignore the larger size clasts. The mean grain size appears to be between 8 to 10 mm. The second method includes counting the number of clasts larger than 2 mm from X-radiographs, and counts of particles (106–1000 μm). These latter counts show that diamictons from the North Iceland shelf indicate a dominance of glacially abraded basaltic grains, but they also contain a small, consistent proportion of angular volcanic glass shards of various compositions. The third method is to examine grain-size spectra of surface samples from East Greenland and the Ross Sea region of Antarctica and compare these data with down-core data from neoglacial-age glacial marine sediments from Nansen Fjord, East Greenland, and with late glacial diamictons from the North Iceland shelf. These sediments have a mode in the silt fraction, but they frequently have secondary peaks in the coarse sand and fine sand/coarse silt areas, and a trough in the range of 100 to 500 μm (medium to coarse sand). Most of the sediment samples analysed in this study contain 20–50% in the below 1 μm grain size, which reinforces the importance of examining this fraction in provenance studies in glacial marine sediments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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".