探索地球内部结构和地震震源机制<bold>——</bold>地震学家<bold>Adam M. Dziewonski</bold>教授的学术成就简介
Bibliographic record
Abstract
Adam M. Dziewonski (1936~2016) 生前是哈佛大学地球与行星科学系教授, 世界著名地球物理学家与地震学家. 鉴于Dziewonski教授在固体地球物理领域的重要基础贡献, 1998年瑞典皇家科学院授予他Crafoord奖(被誉为地学界的“诺贝尔奖”), 1999年美国地震学会授予他Harry Fielding Reid奖章, 2002年美国地球物理学会授予他William Bowie奖章. Dziewonski教授的研究注重于利用地震观测资料来探索地球内部结构和地震震源机制, 他最杰出的工作包括: (1) 发展了地震矩中心位置和震源机制(CMT)反演方法, 建立了实时自动反演全球中大型地震震源参数的系统, 以及具有搜索功能的震源参数数据库以及相关的网站; (2) 发展了被地学界广泛应用的一维地球参考结构模型 PREM; (3) 将层析成像方法应用于地球深部结构的研究中, 反演获得三维非均匀地幔的速度结构模型, 以及地球内部结构间断面的深度起伏特征; (4) 证实地球内核的固态性, 发现地球内核的各向异性和内核最深部的结构特征. Dziewonski教授是很多地震学领域的开创者, 他在地震学基础研究领域的重大贡献深刻而广泛地影响着全世界的地震学家以及其他地球科学领域的研究者. 本文简要介绍了Dziewonski教授主要的科研工作、核心的学术成就及重要的学术服务贡献, 并探讨了他学术研究成功的因素, 希望能够对从事地球科学研究的学者有积极的启示.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.026 | 0.010 |
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".