The Comparison of the National Park Service Between Korea and the US
Bibliographic record
Abstract
The purpose of this research was to demonstrate to the comparison of the National Park Service between Korea and the US. I hope that this research is helpful to those who wish to understand the difference between the two countries and their land and natural resources. Also, I would like to share how to preserve natural and cultural resources between the two countries. The research analyzed the properties, mission, strategy & goal, history, the number of visitors in National Park, budget, employees, the largest/smallest National Park, wildlife (biology), organization, special policy for nature restoration, and restoration project about National Park Service between the two countries. For the past 2 years, I had great experience to learning about the National Park Service in the US. I traveled to every state in the US in the last 2 years except Alaska and Hawaii. I also traveled to east and west area in Canada. Based upon results, the research found that the characteristics of the National Park of Korea look like a charmingly decorated bedroom, but those of the US look like an immense shopping mall. On the other hand, there are many things in common like preserving and restoring of natural resources.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".