Bibliographic record
Abstract
Meteorology is a branch of geophysics that studies the properties of the atmosphere that “cushions” the Earth and all the phenomena that happen within it. The hydrostatic balance occurs when the pressure at any point in the fluid equals the weight of an air column of the unit section from above the point, and in these ideal conditions, we have the hydrostatic equation for the fluid in hydrostatic balance. The hydrostatic equation is viewed as the hydrostatic equilibrium condition, which provides an accurate approximation for the vertical dependence of the pressure field in the real atmosphere. In this talk, we manipulate a mathematical model describing the variation of pressure to altitude in the atmosphere using partial differential equations, and we will show how realistic charts based on real data are obtained, and compare them to charts obtained by using a climate change scenario when the temperature at sea-level is warmer by 2℃ than the one used in current charts. Work done in collaboration with Anneliese Ansorger, Cory Efird, Cassandra Lisitza, Ghristopher Macyk, Tarig Mergani, Adam Reeves, Rebecca Walton, Yaying Zhong, and Jett Ziehe, MacEwan University. Presented in absentia on April 27, 2020 at Student Research Day at MacEwan University in Edmonton, Alberta. (Conference cancelled.) Exhibition held in the Gray Gallery at MacEwan University. Faculty Mentor: Ion Bica Department: Mathematics & Statistics
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".