Bibliographic record
Abstract
深拖曳多道地震勘探系统(DTAGS)由声学和地球物理阵列组成, 具有220~820Hz 的激发震源, 一般拖曳于海底之上300 m 左右的高度. DTAGS 系统具有低于6 m 的勘探波长, 比传统地震勘探更小的第一菲涅尔带半径和更大的波数采样空间, 因此能够提供高分辨率的海底沉积和构造信息. 由于高频扫描和深海拖曳的特殊性, DTAGS 震源和水听器相对位置的精确定位是后续地震成像和速度分析的基础, 因此DTAGS 勘探数据处理质量的关键在于其阵列几何形态的反演. 在北Cascadia 边缘陆坡天然气水合物勘探的实际应用中, DTAGS 系统显示了与低温流体汇集和水合物相关的Cucumber 碳酸盐丘和Bullesye 冷泉构造在横向和纵向上(海底300~400 m 深度范围内)的高分辨率沉积和构造特征, 为评价水合物的资源状况, 研究海底低温热液的运移和汇聚模式, 及其对天然气水合物形成和分布的控制机制, 提供了丰富的信息.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".