南大洋海底地形对冰山运动与搁浅的影响
Bibliographic record
Abstract
冰山是南极冰盖-冰架-海洋系统中活跃的组成部分, 南大洋海底地形是影响冰山运动与搁浅的重要因素, 但前人对此鲜有研究, 本文结合南极Bedmap-2海底地形数据和杨百瀚大学冰山数据库所记录的冰山运动轨迹数据分析了海底地形对冰山运动和搁浅的影响. 结果表明: (1) 冰山搁浅事件与搁浅冰山轨迹点的数量分布主要与冰山水下厚度分布有关, 在水深为200~300m海域内数量最高. 自由运动冰山在南极陆坡锋区域(海洋水深500m左右)存在数量与速度的峰值; (2) 海底地形对冰山运动的直接影响是冰山搁浅, 在沿南极海岸线外围水深低于2000m的362×104km2的海域里, 从冰架前缘崩解的小型冰山可能搁浅区(水深小于400m)占28%即不易搁浅, 这些搁浅区主要分布在东南极与南极半岛沿岸. 从大冰架上崩解的大中型冰山(长轴大于18.5km)可能搁浅区(水深小于800m)占总面积的74%即较易搁浅; (3) 在水深小于2000m的海域内冰山运动速度与海水深度之间具有正相关性(R=0.85, P<0.01)(即海水越深的地方冰山运动越快), 而海冰的季节性变化对这种相关性的影响不大, 说明海底地形起伏所引起的海水深度的变化会对冰山运动速度产生影响.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.006 |
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".