Mineralogical study of surface sediments in the western Arctic Ocean and their implications for material sources
Bibliographic record
Abstract
Mineralogical analysis was performed on bulk sediments of 79 surface samples using X-ray diffraction. The analyticalresults, combined with data on ocean currents and the regional geological background, were used to investigate the mineralsources. Mineral assemblages in sediments and their distribution in the study area indicate that the material sources are complex. (1)Feldspar is abundant in the sediments of the middle Chukchi Sea near the Bering Strait, originating from sediments in the AnadyrRiver carried by the Anadyr Current. Sediments deposited on the western side of the Chukchi Sea are rich in feldspar. Comparedwith other areas, sediments in this region are rich in hornblende transported from volcanic and sedimentary rocks in Siberia by theAnadyr Stream and the Siberian Coastal Current. Sediments in the eastern Chukchi Sea are rich in quartz sourced from sedimentsof the Yukon and Kuskokwim rivers carried by the Alaska Coastal Current. Sediments in the northern Chukchi Sea are rich inquartz and carbonates from the Mackenzie River sediments. (2) Sediments of the southern and central Canada Basin contain littlecalcite and dolomite, mainly due to the small impact of the Beaufort Gyre carrying carbonates from the Canadian Arctic Islands.Compared with other areas, the mica content in the region is high, implying that the Laptev Sea is the main sediment source forthe southern and central Canada Basin. In the other deep sea areas, calcite and dolomite levels are high caused by the input of largeamounts of sediment carried by the Beaufort Gyre from the Canadian Arctic Islands (Banks and Victoria). The Siberian LaptevSea also provides small amounts of sediment for this region. Furthermore, the Atlantic mid-water contributes some fine-grainedmaterial to the entire deep western Arctic Ocean.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".