Bibliographic record
Abstract
The AMS's Board on Higher Education undertook a survey of atmospheric science graduate programs in the United States and Canada during the fall and winter of 2007–08. The survey involved admission data for the three previous years and was performed with assistance from AMS headquarters and in cooperation with the University Corporation for Atmospheric Research (UCAR). Usable responses were received from 29 programs, including most major atmospheric science programs. The responding schools receive between 6 and 140 applications per year, and typical incoming class sizes range from 1 to 24. About 69% of applicants and 76% of enrollees are domestic students. At the majority of schools, all incoming students receive full financial support. The average graduate program looks for undergraduate grade point averages of at least 3.3 to 3.5, higher for nonscience majors. Grade point averages in math and science courses, typically 3.5 or better, are particularly important. The typical midclass GRE of entering graduate students was a combined verbal and quantitative score of 1,300. Larger schools tend to place particular emphasis on math/ science grades and letters of recommendation, while smaller schools typically value a broader range of application characteristics. Students considering graduate school should make a special effort to cultivate potential letter writers, working on research projects if possible. They should also become informed about the particular requirements and values of the programs to which they are applying by visiting them if possible or by contacting professors with active research programs in the student's area of interest.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.263 | 0.064 |
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".